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Turn cutting-edge physics into defence technology This high-growth startup in the defence and security sector is seeking an experimental physicist to work on infrared detection systems. You will build and operate their experimental systems working on all aspects of the design from sensor selection and optical design through to signal processing and data analysis. Your work will directly translate to the technologies and products of the company, and your insights will shape their future research direction. Requirements: Strong hands-on skills building and troubleshooting optical and electronic systems using infrared sensors or detectors. Specific experience with thermal imaging or Long-wave / Medium-Wave / Short-Wave IR would be beneficial but is not required. Good knowledge of signal processing and data analysis methods in the context of imaging processing and object detection. PhD in Physics (or equivalent commercial experience) supported by a top undergraduate degree in Physics (Oxford, Cambridge, Imperial or equivalent). UK national or previous UK security clearance. This is a defence company, and this role requires applicants to be eligible for UK security clearance. This is a great opportunity to further your career working on technically challenging problems with real-world impact. You'll be working alongside other scientists and engineers developing cutting-edge technologies in a stimulating research environment. Keywords: Physics, Experimental, Optics, Imaging Systems, Infrared, Thermal Imaging, LWIR, MWIR, SWIR, Radiometry, Photometry, Signal Processing, Data analysis, Optical Modelling and Simulation, Defence Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV. Please apply (quoting ref: TJ27731 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate. TPBN1_UKTJ

Take your simulation skills beyond academia and into exciting industry challenges This Cambridge based technical team provide expertise in simulation and modelling to industrial and academic groups, helping to solve real-world challenges. They have backgrounds in a wide variety of physics and engineering disciplines from optics and fluid dynamics to structural mechanics and chemical engineering. The team are looking to recruit someone to become an electromagnetics specialist and will consider Master's and PhD holders for the role (candidates with relevant industry experience will also be considered). You will work on projects in fields such as power transmission, medical therapies, and navigation electronics. Alongside direct simulation work you will lead workshops and training sessions as well as providing technical presentations and commercial support. Fundamental knowledge is important as problems can vary greatly, but knowledge of electric motor simulation would be valued. Requirements 1st or 2.1 degree in computational physics, engineering mathematics or applied electronics. Master's or PhD qualification in a relevant subject area. Additional postdoc or industry experience would be beneficial. Excellent fundamental understanding around electromagnetic principles. Ideally, this can be demonstrated through teaching or tutoring of university-level students. Experience with computational simulation / modelling tools (MATLAB, COMSOL, SIMULIA, Simcenter, Octave, etc). Good communication skills (this is a client-facing role, and so being comfortable presenting and discussing technical details is important). Full, unrestricted rights to work in the UK (no company sponsorship is on offer). The role is based at their Cambridge offices. Hybrid working is possible after the first month (possibly up to 3 days per week working from home). Compensation on offer is competitive and includes a range of benefits. The company provides technical training where needed and provides an excellent environment to help transition from academia to industry. Interested applicants do need to have unrestricted rights to work in the UK. Graduate visa holders or those requiring sponsorship will not be considered. Keywords: Electromagnetics, Modelling, Simulation, Electronics, Physics, Training, Demonstrating, Applications Engineering, MSc, PhD, Postdoc Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV. Please apply (quoting ref: TJ27749 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate. TPBN1_UKTJ

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the workloads and benchmarks that reveal how AI infrastructure performs on useful applications. You will develop reproducible LLM serving workloads, connecting application behaviour and requirements to physical measurements and SIL's simulation platform. The initial focus includes long-context inference and agentic workloads. You will investigate how request patterns, context lengths, caching, repeated model calls and interactions with tools shape the demands placed on a system. Your benchmarks will make performance comparisons meaningful by specifying the work being done and the quality and service requirements it must meet. Working with measurement and simulation engineers and our partners, you will help preserve the workload behaviour that matters when moving between real systems and models. Your work will help engineers and investors understand which infrastructure choices suit particular applications, and how conclusions change when the workload changes. • Build and maintain reproducible LLM serving workloads, serving configurations and benchmark tools, including long-context and agentic workloads, using suitable existing software, • Characterise relevant behaviour such as request arrivals, prompt and output lengths, caching, batching, tool interactions and dependencies between requests, • Define performance measures alongside application-quality and service requirements, so comparisons reflect useful work under stated conditions, • Work with measurement engineers to reproduce workloads on physical systems, and with simulator engineers to develop workload representations that preserve the behaviour and dependencies that matter, • Investigate how changes in workloads and serving configurations affect conclusions, and keep the benchmark suite relevant as inference technology and workloads evolve, • Document datasets, model and software versions, configurations, provenance and permitted use so other engineers can reproduce and extend the work, • Experience building or evaluating ML systems, inference services, performance benchmarks or comparable workload-driven systems, • Strong practical software skills for constructing reliable benchmark tools, analysing results and debugging interactions between applications and infrastructure, • Understanding of LLM inference and an interest in how serving choices affect performance and output quality, • Care in designing reproducible comparisons and interpreting results against stated application requirements, • Practical experience using AI coding agents, with the judgement to validate generated code, data transformations and evaluations Experience with vLLM, SGLang or similar serving software, long-context workloads, agentic applications, trace analysis or quality evaluation would be valuable. Depth in a subset is sufficient. The initial remit is LLM serving; other forms of inference are possible later extensions. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Location: Cambridge In-office expectation: Once every two weeks Employment type: Permanent Salary: £55,000-£80,000 This role will be a mid or senior level engineer dependant on experience Redgate's Foundry is our innovation incubator, the team scanning the horizon for Redgate's next big opportunity. This role exists because that kind of work needs engineers who are genuinely excited by discovery: people who can form a hypothesis, test it fast, and make a clear-eyed call on whether to push forward or change course. Most ideas won't become products. That's by design. Each experiment sharpens our thinking and improves the odds of finding the one that will. If you're motivated by that kind of challenge, where the destination isn't fixed and the work is never the same twice, this is the role for you. Redgate brings together people who want to do their best work in an environment built on trust, accountability, and collaboration. We build solutions that help data professionals securely manage the data and databases that their organisations depend on, a space that's only becoming more critical as systems scale, data regulations increase, and AI adoption accelerates. By 2028, Redgate will operate as an expert plus agent company: domain experts amplified by AI, delivering customer value at a pace our peers can't match. AI handles the heavy lifting, and our people control the judgement. Everyone at Redgate works with Claude, giving you access to the best AI tools from day one. • You'll work in a team that cares about collaboration, craft and quality, not just in how we build, but in choosing what to build, finding the shortest path to the questions that matter most., • There’s real scope to grow your skills and impact, with clear pathways and support., • We value sustainable delivery, good ways of working and time to improve how we build. The Foundry operates differently to the rest of Redgate's product teams. You won't be handed a roadmap. Instead, you'll work across the full arc of innovation — from horizon-scanning and ideation through to early-stage research, rapid prototyping, and working directly with customers to validate what you're building. You'll be part of a small cross-functional team (a Tech Lead plus four to six Software and Machine Learning Engineers), and you'll regularly run projects in parallel: contributing to ongoing experiments while also exploring entirely new directions. The tech stack is deliberately varied, the right tool for the job, not a fixed list, spanning C#, TypeScript, Python, and more across desktop, web, API, database, and ML development. • You'll work on problems where there is no established answer and you'll have the autonomy to explore them seriously., • Your work sits at the intersection of software engineering, customer insight, and product thinking; it's rare to find all three in one role., • You'll use and help shape how Redgate adopts agentic coding and AI development tools, not as an afterthought, but as a core part of how the team works., • The scope is genuinely broad: a typical day could see you balancing technical prototypes, customer interviews, and competitor teardowns., • Proven experience using AI coding tools. You've used them extensively, understand their limitations, and have developed ways to work around them productively and safely., • Strong software design and coding skills across modern languages, particularly C#, TypeScript, or Python, enough to guide and review AI-generated code with confidence., • Hands-on experience building agentic systems using frameworks such as LangGraph, Microsoft Agentic Framework, or MCP, with a solid understanding of LLM capabilities and risks., • Experience designing and running experiments to validate ideas quickly, using technical prototypes, customer feedback, and lean startup principles to test assumptions and make clear decisions., • Comfortable engaging directly with customers and stakeholders: running interviews, demos, and concierge-style validation processes, and communicating findings clearly to both technical and non-technical audiences., • A product mindset; you think in terms of user value, outcomes, and market fit, not just features or technical delivery., • Salary range: £55,000-£80,000, • Hybrid working: home and Cambridge office, • Monthly wellbeing allowance and generous paid time off, • Genuine investment in learning, development, and career progression, • Private health insurance Your application will be reviewed by a person, we don't use AI or automated tools to assess applications. Every profile is read by one of our Talent Partners. You’ll hear back within a few days, whether it's a next step or a no, we aim to respond promptly so you're not left wondering. Our interview process is straightforward and consistent, you'll find more detail on our typical hiring process below, so you know what's coming and why. We believe that people do their best work in an environment built on respect, fairness, and trust and that diverse perspectives lead to better outcomes. Redgate is an equal opportunity employer, and we make hiring decisions based on skill, potential, and alignment with our values. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the software that lets SIL configure and control real AI infrastructure for reproducible experiments. You will turn the capabilities of our experimental clusters into programmatic controls for changes such as workload placement, resource allocation and inference-serving configuration. The engineering challenge is making those changes dependable: understanding the current state, checking whether an action can be carried out, confirming what actually happened and handling failures. Your software will make it possible to repeat experiments and understand which configuration produced a result. Working with measurement and simulation engineers and cluster operators, you will establish useful controls for the first experimental studies. Those interfaces will also provide the actions that future design-space optimisation software can call. • Identify the controls available on the selected clusters and expose them through documented, programmatic interfaces with clear supported actions, • Automate configuration and experiment setup across relevant parts of the stack, such as workload placement, serving settings, resource allocation or device configuration, • Build reliable execution with precondition checks, confirmation of the resulting state, error handling and recovery to a known configuration where supported, • Record requested actions, outcomes and resulting configuration so experiments can be reproduced and measurements interpreted correctly, • Coordinate access, permissions and changes with cluster operators, and test success, failure and recovery paths within an agreed experimental scope, • Design interfaces that future optimisation software can call, with clear capability limits and explicit outcomes when an action cannot be completed An example early project would be to build an interface for changing serving configurations and demonstrate a repeatable experiment across two configurations, including checks of the applied settings and recovery from a failed change. • Experience building systems software or automation that configures and controls real computing infrastructure, • Strong programming and debugging skills, with practical understanding of Linux and the relevant hardware/software interfaces, • Depth in one or more of: cluster or HPC automation, distributed systems, orchestration, device control, networking, or experiment-control software, • The ability to reason about partial failure, state, permissions and the consequences of changing a running system, • Practical experience using AI coding agents, with the judgement to validate generated code and test changes that affect hardware or infrastructure Experience with accelerators, job-control systems, Kubernetes, Slurm, operating systems (NixOS, CoreOS) or IaC tools (Terraform/OpenTofu) would be useful. Depth in a subset is sufficient; the initial controls and integration choices will follow the needs and capabilities of SIL's clusters. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the workloads and benchmarks that reveal how AI infrastructure performs on useful applications. You will develop reproducible LLM serving workloads, connecting application behaviour and requirements to physical measurements and SIL's simulation platform. The initial focus includes long-context inference and agentic workloads. You will investigate how request patterns, context lengths, caching, repeated model calls and interactions with tools shape the demands placed on a system. Your benchmarks will make performance comparisons meaningful by specifying the work being done and the quality and service requirements it must meet. Working with measurement and simulation engineers and our partners, you will help preserve the workload behaviour that matters when moving between real systems and models. Your work will help engineers and investors understand which infrastructure choices suit particular applications, and how conclusions change when the workload changes. • Build and maintain reproducible LLM serving workloads, serving configurations and benchmark tools, including long-context and agentic workloads, using suitable existing software., • Characterise relevant behaviour such as request arrivals, prompt and output lengths, caching, batching, tool interactions and dependencies between requests., • Define performance measures alongside application-quality and service requirements, so comparisons reflect useful work under stated conditions., • Work with measurement engineers to reproduce workloads on physical systems, and with simulator engineers to develop workload representations that preserve the behaviour and dependencies that matter., • Investigate how changes in workloads and serving configurations affect conclusions, and keep the benchmark suite relevant as inference technology and workloads evolve., • Document datasets, model and software versions, configurations, provenance and permitted use so other engineers can reproduce and extend the work., • An example early project would be to build a reproducible agentic workload and work with measurement colleagues to compare its performance across two systems, under agreed application-quality and service requirements., • Experience building or evaluating ML systems, inference services, performance benchmarks or comparable workload-driven systems., • Strong practical software skills for constructing reliable benchmark tools, analysing results and debugging interactions between applications and infrastructure., • Understanding of LLM inference and an interest in how serving choices affect performance and output quality., • Care in designing reproducible comparisons and interpreting results against stated application requirements., • Practical experience using AI coding agents, with the judgement to validate generated code, data transformations and evaluations., • Experience with vLLM, SGLang or similar serving software, long-context workloads, agentic applications, trace analysis or quality evaluation would be valuable. Depth in a subset is sufficient. The initial remit is LLM serving; other forms of inference are possible later extensions., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. #J-18808-Ljbffr

CommonAI CIC is a non‑profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build simulation software that helps engineers and investors explore how AI systems would behave with different processors, memory systems, networks or serving strategies. Your work will help turn models and existing software into a practical framework for comparing design choices against realistic LLM workloads. You will develop and connect simulation components, making sure that changes in one part of a system have the appropriate consequences elsewhere. This means understanding unfamiliar code, designing clear interfaces and building software whose predictions can be investigated and tested against measurements. We aim to reuse and extend existing frameworks wherever they provide a sound foundation. We welcome depth in one or more relevant areas, including simulation, systems software, performance modelling and inference serving. Your initial focus will reflect your strengths and the components we choose to build on, with complementary expertise added as the team grows. • Develop and integrate simulation components that capture behaviour and interactions relevant to an AI infrastructure comparison., • Work with the technical lead and our partners to evaluate existing frameworks and software, extending and connecting useful components through clear interfaces., • Develop appropriate models of system state and resource use so that changes in one component have the appropriate consequences elsewhere., • Build reproducible simulation scenarios, diagnostic outputs and tests that expose incorrect assumptions, integration errors and unsupported cases., • Work with measurement and uncertainty colleagues to compare predictions with evidence, improve models and integrate calibration and uncertainty methods into the simulator., • Maintain reliable software, documentation and development workflows, using AI coding agents to support implementation and testing., • An example early project would be to bridge an existing simulator component with our workload models and measurement datasets, producing a reproducible comparison between predicted and measured performance over two systems., • Strong software engineering skills and evidence of building, debugging and maintaining substantial technical software., • Experience in one or more of: discrete‑event simulation; computer architecture or performance modelling; distributed/HPC systems; inference runtimes and serving; memory or network modelling; integration of scientific software and heterogeneous components., • The ability to understand unfamiliar code, reason about interfaces and assess the suitability and maintenance costs of reusing, extending or building software., • A collaborative approach to testing assumptions and working with specialists in adjacent areas., • Practical experience using AI coding agents, with the judgement to check their output for correctness and maintainability. Python, C++, Rust or other relevant systems or scientific programming experience can provide a route into the role. Familiarity with vLLM or SGLang, simulator frameworks, or hardware performance tools would be useful. Depth in a subset of these areas is sufficient; languages and frameworks will follow the engineering needs of the programme. • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part‑time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particular welcome experienced engineers and can also consider earlier‑career with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary…?? CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

In-office expectation: Once every two weeks Employment type: Permanent This role will be a mid or senior level engineer dependant on experience Redgate's Foundry is our innovation incubator, the team scanning the horizon for Redgate's next big opportunity. This role exists because that kind of work needs engineers who are genuinely excited by discovery: people who can form a hypothesis, test it fast, and make a clear-eyed call on whether to push forward or change course. Most ideas won't become products. That's by design. Each experiment sharpens our thinking and improves the odds of finding the one that will. If you're motivated by that kind of challenge, where the destination isn't fixed and the work is never the same twice, this is the role for you. Redgate brings together people who want to do their best work in an environment built on trust, accountability, and collaboration. We build solutions that help data professionals securely manage the data and databases that their organisations depend on, a space that's only becoming more critical as systems scale, data regulations increase, and AI adoption accelerates. • You'll work in a team that cares about collaboration, craft and quality, not just in how we build, but in choosing what to build, finding the shortest path to the questions that matter most., • There’s real scope to grow your skills and impact, with clear pathways and support., • We value sustainable delivery, good ways of working and time to improve how we build. The Foundry operates differently to the rest of Redgate's product teams. You won't be handed a roadmap. Instead, you'll work across the full arc of innovation — from horizon-scanning and ideation through to early-stage research, rapid prototyping, and working directly with customers to validate what you're building. You'll be part of a small cross-functional team (a Tech Lead plus four to six Software and Machine Learning Engineers), and you'll regularly run projects in parallel: contributing to ongoing experiments while also exploring entirely new directions. The tech stack is deliberately varied, the right tool for the job, not a fixed list, spanning C#, TypeScript, Python, and more across desktop, web, API, database, and ML development. • You'll work on problems where there is no established answer and you'll have the autonomy to explore them seriously., • Your work sits at the intersection of software engineering, customer insight, and product thinking; it's rare to find all three in one role., • You'll use and help shape how Redgate adopts agentic coding and AI development tools, not as an afterthought, but as a core part of how the team works., • The scope is genuinely broad: a typical day could see you balancing technical prototypes, customer interviews, and competitor teardowns., • Proven experience using AI coding tools. You've used them extensively, understand their limitations, and have developed ways to work around them productively and safely., • Strong software design and coding skills across modern languages, particularly C#, TypeScript, or Python, enough to guide and review AI-generated code with confidence., • Hands-on experience building agentic systems using frameworks such as LangGraph, Microsoft Agentic Framework, or MCP, with a solid understanding of LLM capabilities and risks., • Experience designing and running experiments to validate ideas quickly, using technical prototypes, customer feedback, and lean startup principles to test assumptions and make clear decisions., • Comfortable engaging directly with customers and stakeholders: running interviews, demos, and concierge-style validation processes, and communicating findings clearly to both technical and non-technical audiences., • A product mindset; you think in terms of user value, outcomes, and market fit, not just features or technical delivery., • Hybrid working: home and Cambridge office, • Monthly wellbeing allowance and generous paid time off, • Genuine investment in learning, development, and career progression, • Private health insurance Your application will be reviewed by a person, we don't use AI or automated tools to assess applications. Every profile is read by one of our Talent Partners. You'll hear back within a few days, whether it's a next step or a no, we aim to respond promptly so you're not left wondering. Our interview process is straightforward and consistent, you'll find more detail on our typical hiring process below, so you know what's coming and why. We believe that people do their best work in an environment built on respect, fairness, and trust and that diverse perspectives lead to better outcomes. Redgate is an equal opportunity employer, and we make hiring decisions based on skill, potential, and alignment with our values. #J-18808-Ljbffr

CommonAI CIC is a non‑profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the software that lets SIL configure and control real AI infrastructure for reproducible experiments. You will turn the capabilities of our experimental clusters into programmatic controls for changes such as workload placement, resource allocation and inference‑serving configuration. The engineering challenge is making those changes dependable: understanding the current state, checking whether an action can be carried out, confirming what actually happened and handling failures. Your software will make it possible to repeat experiments and understand which configuration produced a result. Working with measurement and simulation engineers and cluster operators, you will establish useful controls for the first experimental studies. Those interfaces will also provide the actions that future design‑space optimisation software can call. • Identify the controls available on the selected clusters and expose them through documented, programmatic interfaces with clear supported actions., • Automate configuration and experiment setup across relevant parts of the stack, such as workload placement, serving settings, resource allocation or device configuration., • Build reliable execution with precondition checks, confirmation of the resulting state, error handling and recovery to a known configuration where supported., • Record requested actions, outcomes and resulting configuration so experiments can be reproduced and measurements interpreted correctly., • Coordinate access, permissions and changes with cluster operators, and test success, failure and recovery paths within an agreed experimental scope., • Design interfaces that future optimisation software can call, with clear capability limits and explicit outcomes when an action cannot be completed., • An example early project would be to build an interface for changing serving configurations and demonstrate a repeatable experiment across two configurations, including checks of the applied settings and recovery from a failed change., • Experience building systems software or automation that configures and controls real computing infrastructure., • Strong programming and debugging skills, with practical understanding of Linux and the relevant hardware/software interfaces., • Depth in one or more of: cluster or HPC automation, distributed systems, orchestration, device control, networking, or experiment‑control software., • The ability to reason about partial failure, state, permissions and the consequences of changing a running system., • Practical experience using AI coding agents, with the judgement to validate generated code and test changes that affect hardware or infrastructure., • Experience with accelerators, job‑control systems, Kubernetes, Slurm, operating systems (NixOS, CoreOS) or IaC tools (Terraform/OpenTofu) would be useful. Depth in a subset is sufficient; the initial controls and integration choices will follow the needs and capabilities of SIL's clusters., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part‑time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier‑career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Lead the engineering team building a simulation platform for AI inference systems. You will bring together realistic workloads, hardware models and physical measurements to predict system performance and make the uncertainty in those predictions explicit. The platform will help engineers and investors assess emerging AI infrastructure, understand design choices, and identify next experiments. You will turn scientific direction into an implementable architecture and delivery plan, help shape recruitment, and develop a team with complementary expertise across software, modelling, measurement and hardware. You will report to the SIL Scientific Director and line manage a group of engineers in the growing SIL team. Working closely with the Director of Engineering, you will provide daily technical leadership and help shape the team as we recruit. Technical judgement and the ability to bring people with you matter more than having held a particular management title in the past. • Own the simulator codebase, working closely with the Scientific Director, SIL on architectural decisions. Translate the programme's scientific goals into an achievable engineering roadmap., • Assess existing simulators, serving software and partner components; decide what to reuse, extend or build, and establish interfaces that make the pieces work together., • Shape recruitment, assess candidates and mentor colleagues and line-manage engineers, building complementary expertise across software, measurement, modelling and hardware., • Ensure simulator predictions are tested against physical measurements and realistic LLM workloads, with uncertainty made explicit to the people interpreting the results., • Establish engineering practices for maintainable software, testing, reproducible experiments and effective use of AI coding agents; review designs and results with the relevant specialists., • Contribute directly to implementation and debugging when engineering coverage is incomplete or a colleague needs support. An example early project would be to lead a complete study from an investor's question through simulation and measured validation to a useful evidence report, while establishing the team and foundations for subsequent cases. • Substantial industrial engineering experience delivering complex software or hardware/software systems, with clear examples of technical decisions you have owned., • Depth in at least one of systems simulation, computer architecture, distributed or HPC systems, inference serving, or experimental performance engineering. Experience across more than one is especially valuable., • Evidence that you can lead people through difficult technical work, explain trade-offs and develop others. This may come from technical leadership and mentoring as well as formal management., • The judgement to turn high-level scientific direction into independent engineering decisions, and to recognise when wider input is needed., • Practical engineering ability to review code and designs, investigate failures and help colleagues resolve implementation difficulties., • Experience using AI coding agents, with the ability to assess their output and help colleagues use them effectively. Experience connecting research prototypes to maintained engineering systems, collaborating with universities or technology suppliers, and comparing models with measurements would be valuable. We do not expect you to be the deepest specialist in every part of the programme. • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid working, with Cambridge attendance agreed individually around collaboration and job need. We would like you to start as soon as practical and can be flexible for the right person. We value engineering quality and demonstrated leadership over a particular qualification or previous management title. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Help evaluate proposed AI hardware before it is available as a finished chip. You will turn RTL designs into working FPGA prototypes and emulation experiments, giving SIL and its technology partners a practical way to explore design behaviour and architectural choices. The initial focus is on RTL prototyping and emulation. You will help choose a useful first design and platform, adapt and integrate the RTL, and establish repeatable build, bring-up and experimental workflows. Working with our partners and colleagues in software and simulation, you will connect observations from the prototypes to wider system studies. Your work will help establish what the experiments tell us about a proposed design, how those findings relate to simulator models and where further evidence is needed. • Adapt and integrate RTL for FPGA prototyping or emulation, working with the design owners and documenting changes needed for the prototype., • Develop and maintain synthesis, implementation, timing-closure and reproducible build flows for the selected platform., • Bring up and debug designs, developing tests and instrumentation to check functional behaviour and support repeatable experiments., • Develop or integrate the control, stimulus and data-capture facilities needed for the agreed experiments, working with software colleagues on host interfaces and integration., • Relate observations from emulation to the model being evaluated, explaining how prototype frequency, interface overheads and other limitations affect interpretation., • Help assess platform, toolchain and hardware requirements, and document workflows that colleagues and partners can reuse. An example early project would be to take a partner's RTL design through FPGA implementation and bring-up, then instrument it to investigate a selected architectural choice and compare observations with a simulator model. • Hands-on experience taking RTL through an FPGA prototyping or emulation flow and debugging the resulting system., • Strong digital-design skills in Verilog, SystemVerilog, VHDL or an equivalent HDL, together with practical timing and verification judgement., • Experience with a relevant FPGA or emulation toolchain and the scripting needed to make builds and experiments repeatable., • The ability to collaborate across hardware and software boundaries and explain the conclusions and limitations of a prototype experiment., • Practical experience using AI coding agents, with the judgement to validate generated HDL, scripts and software., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier‑career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Our world is transforming, and PTC is leading the way. Our software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business. Our people make all the difference in our success. Today, we are a global team of nearly 7,000 and our main objective is to create opportunities for our team members to explore, learn, and grow – all while seeing their ideas come to life and celebrating the differences that make us who we are and the work we do possible. About the team The Pipeline squad owns the infrastructure, build, release, and security foundations that every other Jetstream squad builds on top of. Jetstream is a NestJS + Angular monorepo deployed into Azure Kubernetes via Helm, shipped through GitLab CI/CD, and running on the wider PTC Atlas platform. We're the squad that makes shipping fast, safe, and boring so product squads can focus on features. • Work on services from development through to deployment and running them in production., • Build and maintain backend services, mainly using TypeScript, Node.js and NestJS., • Help improve our GitLab CI/CD pipelines, including build, test, security and deployment., • Work with Docker, Kubernetes and Helm to deploy and troubleshoot our services., • Improve developer tooling and workflows, particularly where we can remove manual work or make things simpler., • Help improve observability, monitoring and debugging across our services., • Work alongside DevOps on infrastructure and automation where needed, including things like Terraform and Azure., • Generally be comfortable working across backend development, CI/CD and the platform rather than focusing only on application code., • Strong backend development experience, ideally TypeScript/Node.js/NestJS., • Good CI/CD experience, ideally GitLab CI., • Good experience with Docker and some practical Kubernetes experience., • Experience deploying and troubleshooting services, not just developing them locally., • A good understanding of testing, debugging, logging and monitoring., • Comfortable working across application and infrastructure/deployment areas., • Helm, Terraform and Azure/AKS experience would be useful, but I wouldn't make all of these hard requirements., • Experience with PostgreSQL, APIs and asynchronous/messaging systems would also be useful given the services we work with., • Experience creating agentic development workflows or writing and maintaining AI skills., • npm workspaces / shared-package build systems., • Experience supporting SaaS platforms with strict data-privacy requirements (enterprise/multinational customers). We favor paved paths and sensible defaults over teams maintaining highly custom setups. Simplicitiy - the art of maximising the amount of work not done - is essential. Developers work end-to-end to solve customer problems, and our tooling encourages end-to-end workflows over platform components. Life at PTC is about more than working with today’s most cutting-edge technologies to transform the physical world. It’s about showing up as you are and working alongside some of today’s most talented industry leaders to transform the world around you. Life at PTC is about more than working with today’s most cutting-edge technologies to transform the physical world. It’s about showing up as you are and working alongside some of today’s most talented industry leaders to transform the world around you. If you share our passion for problem-solving through innovation, you’ll likely become just as passionate about the PTC experience as we are. We respect the privacy rights of individuals and are committed to handling Personal Information responsibly and in accordance with all applicable privacy and data protection laws. Review our Privacy Policy here. PTC is a global software company powering how products are designed, built, serviced, and operated across industries like Aerospace & Defense, Industrial, Automotive, MedTech, Electronics, and High Tech. We are bold thinkers who collaborate as one team to deliver meaningful customer outcomes. Grounded in our values-Customers Matter, PTC for All, Team PTC, Purposeful Innovation, and Be Bold, we're shaping a smarter, more sustainable, connected future. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Make uncertainty a first-class output of an AI systems simulator. When a simulation predicts that one design will outperform another, you will help establish how much confidence the evidence supports, which assumptions could change the conclusion, and which experiments would reduce the uncertainty that matters to the decision. You will combine mathematical reasoning with practical software engineering to calibrate models against measurements, test predictions on independent cases and build uncertainty analysis into the simulation workflow. Your methods and software will help engineers and investors understand what the simulator predicts and the limits of those predictions. We welcome people from AI systems, HPC and other fields where simulation is tested against experiments. You might bring systems engineering experience and an interest in developing uncertainty methods, or experience in mathematical modelling and scientific computing that you want to apply to AI infrastructure. • Develop and implement methods to calibrate simulator models against measurements and evaluate predictions on cases that were not used for calibration., • Distinguish uncertainty arising from measurements, model assumptions and parameters, operational variation and limited simulation runs, and represent it appropriately., • Analyse sensitivity and uncertainty in comparisons between alternatives, accounting for shared sources of uncertainty and their effects on the comparison., • Develop outputs that show how uncertain a prediction is, when a ranking could change, and when a result extends beyond the evidence used to validate it., • Work with measurement and workload engineers to design experiments that test modelling assumptions and reduce uncertainty that matters to the decision., • Integrate these methods into repeatable simulation workflows and communicate their assumptions and limitations to engineers and the technical analyst., • An example early project might be to establish a calibration and validation workflow for the a comparison between two architectures, with uncertainty outputs that help explain the result. You will develop and review the methodology with the technical lead and Scientific Director, SIL., • Mathematical maturity: the ability to reason carefully about models, data, variation and the assumptions behind a quantitative claim., • Software engineering experience sufficient to turn numerical methods or analysis into readable, tested, reusable tools., • Relevant experience in one or more of: quantitative systems performance analysis, statistical modelling, simulation validation, uncertainty quantification, scientific/HPC software or the theory of experimental design., • The ability to collaborate with specialists and explain both a result and the limits of the evidence supporting it., • Practical experience using AI coding agents and checking their output., • Experience with model discrepancy, sensitivity analysis, Bayesian methods, surrogate models or sequential experimental design would be useful. So would familiarity with computer architecture or inference systems. We welcome complementary backgrounds: strong systems engineers developing uncertainty expertise, and engineers with modelling or uncertainty expertise moving into AI infrastructure., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. #J-18808-Ljbffr

Electrical Site Services Engineer Monday to Friday Days | 7:30am - 4:00pm Salary: £48,000 Location: Poole, Dorset Are you an electrically qualified Maintenance Engineer looking to move away from shift work into a Monday-to-Friday days role? Do you have experience maintaining electrical infrastructure, industrial utilities or building services within a manufacturing or facilities environment? We're working with a leading UK food manufacturer to recruit an Electrical Site Services Engineer to join their established engineering team in Poole. This is an excellent opportunity for an experienced Electrical Engineer who enjoys varied, hands-on maintenance work and wants to take ownership of the electrical systems that keep a large manufacturing facility running. You'll be working across a wide range of site services and utilities, including electrical distribution systems, switchgear, control panels, industrial boilers, compressors, pumps, refrigeration and ventilation systems. Unlike a traditional production maintenance position, your focus will be on the site's electrical infrastructure, utilities and building services, ensuring essential equipment remains safe, reliable and fully operational. This is what you'll be doing: As an Electrical Site Services Engineer, you'll play a key role in maintaining and improving the site's electrical infrastructure, utilities and associated building services. Responsibilities: Carry out planned and reactive electrical maintenance across site services, utilities and building infrastructure. Diagnose and repair electrical faults across three-phase systems, motors, control panels, contactors, relays, inverters and associated electrical equipment. Maintain and inspect electrical distribution systems, switchgear, distribution boards, isolators and associated infrastructure. Support the maintenance of industrial utilities, including the electrical systems associated with boilers, compressors, refrigeration plant, pumps and ventilation equipment. Carry out electrical installation work, component replacements, modifications and upgrades across the site. Read and interpret electrical drawings and schematics to identify faults and support maintenance activities. Support electrical compliance activities, including inspection, testing, preventative maintenance and safe isolation procedures. Coordinate external contractors and specialist service providers, ensuring all work is completed safely and to the required standards. Identify opportunities to improve equipment reliability, energy efficiency and site infrastructure, supporting ongoing improvement projects. The experience you'll bring: We're looking for an electrically qualified engineer with strong fault-finding skills and experience working with industrial electrical systems. Ideally, you'll have: A recognised electrical engineering qualification, such as NVQ Level 3, City & Guilds or equivalent. Previous experience within manufacturing, industrial facilities, utilities or building services maintenance. Strong electrical fault-finding skills across three-phase systems, motors, control panels and associated electrical equipment. Experience maintaining electrical distribution systems, switchgear, distribution boards or industrial electrical installations. Confidence reading and interpreting electrical drawings and schematics. A good understanding of electrical safety, safe isolation and permit-to-work procedures. Experience supporting the electrical maintenance of industrial utilities, such as compressors, boilers, refrigeration systems, pumps or ventilation equipment. Desirable qualifications and experience: 18th Edition Wiring Regulations. City & Guilds 2391 Inspection and Testing. Experience with building management systems (BMS). Previous involvement in electrical installation projects, site upgrades or contractor management. And this is what you'll get in return: Salary £48,000 Monday to Friday days (7:30am - 4:00pm) No regular night shifts or weekend working Electric vehicle salary sacrifice scheme Cycle to Work and Home & Tech salary sacrifice schemes Online and high street retailer discounts Access to health and wellbeing support services Ongoing technical training and development opportunities Company mentoring scheme Free products and employee rewards Long-term stability within an established UK food manufacturer Are you up to the challenge? If you're an electrically qualified Maintenance Engineer, Electrical Technician or Site Services Engineer looking for a varied, days-based role with a strong focus on electrical infrastructure and industrial utilities, we'd love to hear from you. This opportunity could suit engineers from manufacturing, facilities management, building services or industrial maintenance backgrounds who enjoy hands-on electrical work and want to develop their skills across a diverse range of site services equipment. Apply today with your CV to find out more. Please note, whilst we do our best to contact all candidates, due to the high number of applications we receive, we cannot guarantee this for every role. If you have not heard anything from us within 7 days of applying, unfortunately you have been unsuccessful. Please keep an eye on our website for more opportunities. JBRP1_UKTJ

Lead modernisation projects on web applications for science research platform Duxford, Cambridge; c£60,000 DoE + Benefits Take a leading role as a Senior Developer to realise innovative web products as part of the company's new digital transformation. The company is at the forefront of science research in the UK, and put high priority in having clear public communications and news of their successes to elicit further future support. Leading their new web application projects, you will take a critical hands-on approach to shape this. The focus for projects is on the user experience and utilising modern web technologies to optimise its overall visibility and stakeholder engagement. The role will be both hands-on combined with technical leadership, contributing to design, build, test, optimisation and operation. Requirements: Experience as a senior or lead level full stack developer, with demonstrable projects using modern web technologies including a strong focus on front end development (this should include the use of React and ideally Next.js as well as Python or Django). Additionally, have experience or some exposure to Headless CMS and API driven architectures, as well as use of CI/CD pipelines and automated testing practices. Good communication skills and experience working with external technical stakeholders. Hybrid working is an option, with minimally 2 days in the office. Other flexible full-time working arrangements are possible. Full, unrestricted rights to work in the UK are required, no company sponsorship. This role is initially for 24 months, with the possibilities of extension to be discussed near the end of this term. The company support diversity and will make every allowance where possible (within their business framework). Keywords: Full Stack Web Platform, Modern Technology, React, Next.js, Headless, Python / Django, Cloud, 24 Months FTC Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV. Please apply (quoting ref: TJ27719 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate. TPBN1_UKTJ

Writing robust Python software for AI applications on hardware technologies This rapidly expanding defence start-up develops AI-based hardware products. They are recruiting in a number of areas and are looking to recruit an experienced / junior Software Engineer to join their team. As their next Software Engineer hire, you would join a team that are working on early-stage prototypes as well as more mature product technologies. The position is fully hands-on and requires a good sense of understanding and experience for task prioritisation, as well as ability to work on projects concurrently. Requirements: - 1st in Computer Science or similar from a top Russell Group university (MSc or PhD would be desirable). This should also include A/A* A-levels in Maths and Physics. - Extensive demonstrable experience using Python for complex prototyping and / or production code (relevant internship experience would be highly beneficial). Must have the aptitude to pick up new languages and technologies when needed. - Experience with hardware devices or sensors. Any experience with embedded systems, mobile OS or computer networking would be beneficial. - Experience with deep-learning frameworks (TensorFlow or PyTorch) would be desirable. - Exposure to computational statistics, algorithm development or machine learning optimisation would be a bonus. Due to projects being related to defence applications, candidates must be British nationals, resident in the UK for the past 5 years and eligible for security clearance. The office for this role is currently based south of Cambridge (with plans to relocate in the near future to Cambridge) and this role would require candidates to be fully onsite. Due to the company having multiple office locations, they are wanting candidates to have a driving licence or are in the process of obtaining a licence. On offer is a competitive salary package, and the opportunity to work on interesting projects that will challenge you technically and allow you to develop your skills and knowledge with like-minded engineers. Keywords : Python, PyTorch, TensorFlow, Sensors, Embedded Systems, Hardware Interface, Mobile OS, Algorithms, Statistics, Machine Learning, Defence, Security Clearance, Start Up Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV. Please apply (quoting ref: TJ27735 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate. TPBN1_UKTJ

Provide remote and on-site customer support for defence applied technology products South Cambridgeshire - onsite; c£28,000 to c£38,000 DoE Are you looking for a varied role that harnesses your interest in technology and natural inquisitiveness and people skills? This defence technology company has developed electro-optical sensor applications on top of a proprietary AI platform. They are looking for bright, capable people to join their technical support engineering team to help product deployment at their customer sites. This would include management of infrastructure, performance monitoring and troubleshooting technical issues. Aptitude and attitude are key for success in this role, as technology will be novel and evolving. Requirements: 1st in computer science, electronics, physics, maths or mechatronic engineering from a Russell Group university (this should be supported with A*/As at A-level in maths and physics). Interest in technology including AI and robotics through hobby projects or other extra-curricular activities. Project experience (ideally in industry) working on technical problems involving other stakeholders. Must evidence good communication skills. Good ability to prioritise projects through excellent organisational skills. Cloud or Linux computer networking / monitoring experience (ideally AWS, Prometheus). Driving licence and ability to travel to client sites when required. Specific technical training will be provided, and so interested candidates do need to evidence a background of high academic achievement and leadership qualities. The role requires eligibility for security clearance, and would be fully onsite at offices just south of Cambridge. On offer is a good compensation package, but moreover the opportunity to launch your career with this growing start-up. Keywords: Cloud, Computer Networking, Linux, Technical Support, Problem Solving, Leadership, Communications, Security Clearance, Defence, Travel, Onsite Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV. Please apply (quoting ref: TJ27742 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate. TPBN1_UKTJ

Our world is transforming, and PTC is leading the way. Our software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business. Our people make all the difference in our success. Today, we are a global team of nearly 7,000 and our main objective is to create opportunities for our team members to explore, learn, and grow – all while seeing their ideas come to life and celebrating the differences that make us who we are and the work we do possible. About the team The Pipeline squad owns the infrastructure, build, release, and security foundations that every other Jetstream squad builds on top of. Jetstream is a NestJS + Angular monorepo deployed into Azure Kubernetes via Helm, shipped through GitLab CI/CD, and running on the wider PTC Atlas platform. We're the squad that makes shipping fast, safe, and boring so product squads can focus on features. • Work on services from development through to deployment and running them in production., • Build and maintain backend services, mainly using TypeScript, Node.js and NestJS., • Help improve our GitLab CI/CD pipelines, including build, test, security and deployment., • Work with Docker, Kubernetes and Helm to deploy and troubleshoot our services., • Improve developer tooling and workflows, particularly where we can remove manual work or make things simpler., • Help improve observability, monitoring and debugging across our services., • Work alongside DevOps on infrastructure and automation where needed, including things like Terraform and Azure., • Generally be comfortable working across backend development, CI/CD and the platform rather than focusing only on application code., • Strong backend development experience, ideally TypeScript/Node.js/NestJS., • Good CI/CD experience, ideally GitLab CI., • Good experience with Docker and some practical Kubernetes experience., • Experience deploying and troubleshooting services, not just developing them locally., • A good understanding of testing, debugging, logging and monitoring., • Comfortable working across application and infrastructure/deployment areas., • Helm, Terraform and Azure/AKS experience would be useful, but I wouldn't make all of these hard requirements., • Experience with PostgreSQL, APIs and asynchronous/messaging systems would also be useful given the services we work with., • Experience creating agentic development workflows or writing and maintaining AI skills., • npm workspaces / shared-package build systems., • Experience supporting SaaS platforms with strict data-privacy requirements (enterprise/multinational customers). We favor paved paths and sensible defaults over teams maintaining highly custom setups. Simplicitiy - the art of maximising the amount of work not done - is essential. Developers work end-to-end to solve customer problems, and our tooling encourages end-to-end workflows over platform components. Life at PTC is about more than working with today’s most cutting-edge technologies to transform the physical world. It’s about showing up as you are and working alongside some of today’s most talented industry leaders to transform the world around you. Life at PTC is about more than working with today’s most cutting-edge technologies to transform the physical world. It’s about showing up as you are and working alongside some of today’s most talented industry leaders to transform the world around you. If you share our passion for problem-solving through innovation, you’ll likely become just as passionate about the PTC experience as we are. We respect the privacy rights of individuals and are committed to handling Personal Information responsibly and in accordance with all applicable privacy and data protection laws. Review our Privacy Policy here. PTC is a global software company powering how products are designed, built, serviced, and operated across industries like Aerospace & Defense, Industrial, Automotive, MedTech, Electronics, and High Tech. We are bold thinkers who collaborate as one team to deliver meaningful customer outcomes. Grounded in our values-Customers Matter, PTC for All, Team PTC, Purposeful Innovation, and Be Bold, we're shaping a smarter, more sustainable, connected future. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the workloads and benchmarks that reveal how AI infrastructure performs on useful applications. You will develop reproducible LLM serving workloads, connecting application behaviour and requirements to physical measurements and SIL's simulation platform. The initial focus includes long-context inference and agentic workloads. You will investigate how request patterns, context lengths, caching, repeated model calls and interactions with tools shape the demands placed on a system. Your benchmarks will make performance comparisons meaningful by specifying the work being done and the quality and service requirements it must meet. Working with measurement and simulation engineers and our partners, you will help preserve the workload behaviour that matters when moving between real systems and models. Your work will help engineers and investors understand which infrastructure choices suit particular applications, and how conclusions change when the workload changes. • Build and maintain reproducible LLM serving workloads, serving configurations and benchmark tools, including long-context and agentic workloads, using suitable existing software., • Characterise relevant behaviour such as request arrivals, prompt and output lengths, caching, batching, tool interactions and dependencies between requests., • Define performance measures alongside application-quality and service requirements, so comparisons reflect useful work under stated conditions., • Work with measurement engineers to reproduce workloads on physical systems, and with simulator engineers to develop workload representations that preserve the behaviour and dependencies that matter., • Investigate how changes in workloads and serving configurations affect conclusions, and keep the benchmark suite relevant as inference technology and workloads evolve., • Document datasets, model and software versions, configurations, provenance and permitted use so other engineers can reproduce and extend the work., • An example early project would be to build a reproducible agentic workload and work with measurement colleagues to compare its performance across two systems, under agreed application-quality and service requirements., • Experience building or evaluating ML systems, inference services, performance benchmarks or comparable workload-driven systems., • Strong practical software skills for constructing reliable benchmark tools, analysing results and debugging interactions between applications and infrastructure., • Understanding of LLM inference and an interest in how serving choices affect performance and output quality., • Care in designing reproducible comparisons and interpreting results against stated application requirements., • Practical experience using AI coding agents, with the judgement to validate generated code, data transformations and evaluations., • Experience with vLLM, SGLang or similar serving software, long-context workloads, agentic applications, trace analysis or quality evaluation would be valuable. Depth in a subset is sufficient. The initial remit is LLM serving; other forms of inference are possible later extensions., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Design and run experiments that reveal how AI infrastructure behaves, what limits its performance and how reliably that behaviour can be predicted. You will build measurement tools and turn observations of real hardware and software into evidence for SIL’s simulation platform and the investment decisions it supports. Your work will range from targeted experiments on individual components to measurements of complete LLM serving systems. Working with workload, simulation and uncertainty specialists, you will investigate bottlenecks, explain performance variation and identify the meaningful effects. We welcome deep expertise in one or more parts of the hardware and software stack. You will work with colleagues who bring complementary strengths, with scope to broaden your expertise as the team grows. • Design and run reproducible experiments, from individual hardware or software components to complete LLM serving systems, covering relevant workloads, configurations and operating conditions., • Develop reusable measurement tools and collect traces, profiles and counters to characterise latency, throughput, memory behaviour and, where reliable measurement is possible, power and energy., • Investigate bottlenecks, performance variation and unexpected behaviour across the layers your expertise covers, working with colleagues to extend the investigation through the stack., • Take responsibility for reproducible workload details, software versions, configuration and measurement methods so results can be reproduced, compared and used to calibrate simulator models., • Work with simulation and uncertainty specialists to choose measurements that resolve important unknowns and undertake curation of calibration and validation data., • Help define the controls needed for experiments and use the resulting cluster-control interfaces, coordinating access and changes with colleagues responsible for the hardware. An example early project would be to work with workload colleagues to establish a reproducible reference experiment and measurement dataset, investigating how performance changes under a selected configuration or load change. • Experience investigating the performance of real computing systems and designing experiments that support rigorous conclusions., • Depth in one or more relevant areas: accelerator profiling, inference runtimes, memory systems, distributed/HPC workloads, networking, or power and energy measurement., • The ability to build maintainable automation and analysis tools in a suitable software language, and to learn unfamiliar profiling tools., • Knowledge and care of experimental controls, repeatability, confounding effects and the limits of a measurement., • Some experience using AI coding agents, alongside sound debugging and review habits. LLM serving experience and familiarity with tools such as Nsight, PyTorch Profiler or system/network profilers would be useful. These are examples, not a requirement to know every tool. Strong expertise in one part of the stack is welcome; we can shape the role and recruit complementary strengths around it. • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

CommonAI CIC is a non‑profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build simulation software that helps engineers and investors explore how AI systems would behave with different processors, memory systems, networks or serving strategies. Your work will help turn models and existing software into a practical framework for comparing design choices against realistic LLM workloads. You will develop and connect simulation components, making sure that changes in one part of a system have the appropriate consequences elsewhere. This means understanding unfamiliar code, designing clear interfaces and building software whose predictions can be investigated and tested against measurements. We aim to reuse and extend existing frameworks wherever they provide a sound foundation. We welcome depth in one or more relevant areas, including simulation, systems software, performance modelling and inference serving. Your initial focus will reflect your strengths and the components we choose to build on, with complementary expertise added as the team grows. • Develop and integrate simulation components that capture behaviour and interactions relevant to an AI infrastructure comparison., • Work with the technical lead and our partners to evaluate existing frameworks and software, extending and connecting useful components through clear interfaces., • Develop appropriate models of system state and resource use so that changes in one component have the appropriate consequences elsewhere., • Build reproducible simulation scenarios, diagnostic outputs and tests that expose incorrect assumptions, integration errors and unsupported cases., • Work with measurement and uncertainty colleagues to compare predictions with evidence, improve models and integrate calibration and uncertainty methods into the simulator., • Maintain reliable software, documentation and development workflows, using AI coding agents to support implementation and testing., • An example early project would be to bridge an existing simulator component with our workload models and measurement datasets, producing a reproducible comparison between predicted and measured performance over two systems., • Strong software engineering skills and evidence of building, debugging and maintaining substantial technical software., • Experience in one or more of: discrete‑event simulation; computer architecture or performance modelling; distributed/HPC systems; inference runtimes and serving; memory or network modelling; integration of scientific software and heterogeneous components., • The ability to understand unfamiliar code, reason about interfaces and assess the suitability and maintenance costs of reusing, extending or building software., • A collaborative approach to testing assumptions and working with specialists in adjacent areas., • Practical experience using AI coding agents, with the judgement to check their output for correctness and maintainability. Python, C++, Rust or other relevant systems or scientific programming experience can provide a route into the role. Familiarity with vLLM or SGLang, simulator frameworks, or hardware performance tools would be useful. Depth in a subset of these areas is sufficient; languages and frameworks will follow the engineering needs of the programme. • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part‑time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particular welcome experienced engineers and can also consider earlier‑career with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary…?? CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

CommonAI CIC is redefining deep-tech AI solutions through collaborative engineering and shared infrastructure. Working at the intersection of AI, cloud and large-scale infrastructure, we partner with commercial, government and research entities to accelerate AI adoption across the UK and Europe. Backed by UK Government and private funding, our team of experienced founders and engineers is building the future of AI systems. Its members include ARIA, Barclays and a fast-growing group of deeptech startups. Highly regulated industries like financial services need guaranteed, predictable outcomes that today's large language models cannot provide on their own. Our High Assurance programme will develop AI systems which can be used safely in environments where accuracy and explainability are critical building blocks in creating a required level of trust. The programme is exploring several approaches, including: • Formal methods and verification: proofs that an AI system must satisfy before it can act, • Domain-specific small language models for regulated use cases, • AI control platforms that govern how AI systems behave in production The programme launched recently, with Barclays as its lead member and held its first workshop, "Towards Trustworthy Harnesses", with members, academics and domain experts. We are looking for a Programme Technical Lead to drive execution of the High Assurance AI Programme. The programme already has an academic architectural lead; this role turns the programme's research direction into delivered engineering, working closely with the architectural lead, our Chief Science Officer and our members. You will report to the CTO and build and lead the programme's engineering team. • Own delivery of the programme's technical roadmap, from research direction to working infrastructure, • Build, hire and lead an engineering team based in Cambridge, • Translate the needs of regulated industries into clear technical requirements, making sure the programme solves the problems which matter to members, • Bring members, researchers and partners together around a shared roadmap, • Work with the architectural lead to evaluate approaches such as formal methods, AI control and small language models and decide what to build, • Represent the programme technically with members and partners We do not expect anyone to have all of the experience below. Deep expertise in one area, combined with the ability to work across the others, matters more than ticking every box. • Understanding/experience of processes/workflows (and their associated constraints) in the financial services industry, particularly banks, • Understanding of how AI is or might be used, governed or assured in a regulated industry, ideally financial services (for example model risk, AI governance or controls), • Experience with PyTorch or other similar frameworks, • Enough technical depth to engage credibly with ML researchers and understand the problems the programme needs to solve, without needing to be the person who writes the proofs or algorithms, • Ability to bring together organisations with different priorities and build a shared plan, • Experience leading an engineering team and driving delivery in a technical, research-driven environment, • Experience with formal methods, verification, AI safety, AI assurance or AI control, • Experience with small or domain-specific language models, • Relationships with banks, insurers or regulators, • Experience in a startup, or building a new product, or independent project / research that has resulted in software used by others, • Lead a new programme at the boundary of research and industry, helping to solve tough challenges such as how AI can be used safely in critical industries, • High-impact role in a rapidly growing, well-funded organisation, • Mission-led work for the public good, released over time as managed open source, • Competitive salary, pension, healthcare and benefits, including company share scheme, • Networking opportunities with leaders across tech and academia, • Vibrant office situated near to Cambridge train station CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Help evaluate proposed AI hardware before it is available as a finished chip. You will turn RTL designs into working FPGA prototypes and emulation experiments, giving SIL and its technology partners a practical way to explore design behaviour and architectural choices. The initial focus is on RTL prototyping and emulation. You will help choose a useful first design and platform, adapt and integrate the RTL, and establish repeatable build, bring-up and experimental workflows. Working with our partners and colleagues in software and simulation, you will connect observations from the prototypes to wider system studies. Your work will help establish what the experiments tell us about a proposed design, how those findings relate to simulator models and where further evidence is needed. • Adapt and integrate RTL for FPGA prototyping or emulation, working with the design owners and documenting changes needed for the prototype, • Develop and maintain synthesis, implementation, timing-closure and reproducible build flows for the selected platform, • Bring up and debug designs, developing tests and instrumentation to check functional behaviour and support repeatable experiments, • Develop or integrate the control, stimulus and data-capture facilities needed for the agreed experiments, working with software colleagues on host interfaces and integration, • Relate observations from emulation to the model being evaluated, explaining how prototype frequency, interface overheads and other limitations affect interpretation, • Help assess platform, toolchain and hardware requirements, and document workflows that colleagues and partners can reuse An example early project would be to take a partner's RTL design through FPGA implementation and bring-up, then instrument it to investigate a selected architectural choice and compare observations with a simulator model. • Hands-on experience taking RTL through an FPGA prototyping or emulation flow and debugging the resulting system, • Strong digital-design skills in Verilog, SystemVerilog, VHDL or an equivalent HDL, together with practical timing and verification judgement, • Experience with a relevant FPGA or emulation toolchain and the scripting needed to make builds and experiments repeatable, • The ability to collaborate across hardware and software boundaries and explain the conclusions and limitations of a prototype experiment, • Practical experience using AI coding agents, with the judgement to validate generated HDL, scripts and software Experience with processor or accelerator designs, multi-FPGA partitioning, host interfaces or performance characterisation would be useful. Depth with a relevant platform is sufficient; the team will choose the initial platform and design around the first useful study. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Senior Electronics Engineer - Cambridge If you're the type of engineer who enjoys taking a concept scribbled on a whiteboard and turning it into a real, manufactured product, this could be worth a look. We're working with an established Cambridge technology company that develops innovative products for global organisations across a range of high-tech sectors. One project might involve electronics for a complex electromechanical system, the next could see you solving a completely different technical challenge for an international customer. This isn't a role where you'll spend years making minor updates to a legacy product. Instead, you'll work alongside a multidisciplinary team of talented engineers, scientists and designers developing new products from concept through to manufacture. The role would suit an experienced Electronics Engineer who enjoys hands-on product development and embedded software, and is keen to increase their influence on projects whilst remaining technically involved. Senior Electronics Engineer - What you'll be doing • Electronic circuit design and development, • Embedded software development (C/C++), • Prototyping, testing and problem solving, • Working as part of multidisciplinary product development teams, • Supporting products from concept through to manufacture, • Presenting technical progress internally and to customers, • Increasing involvement in technical leadership and project ownership as your role develops Senior Electronics Engineer - We'd like to see • Commercial experience designing electronic systems, • Embedded software development experience, • Strong practical electronics skills, • Enjoyment of hands-on engineering and problem solving, • Good communication skills and ability to work across disciplines, • A strong academic background in Electronic Engineering or a related discipline Particularly interesting backgrounds We're keen to speak with engineers who have developed real products rather than purely theoretical designs. That could include experience within: • Electronics product development, • Embedded systems, • Medical devices, • Instrumentation, • Scientific equipment, • Robotics, • Industrial electronics, • Consumer products Why people join Engineers who thrive here tend to be curious, practical and enjoy variation. You'll gain exposure to a broad range of technologies, work closely with experienced multidisciplinary teams and have genuine opportunities to influence technical direction whilst continuing to develop your own skills. Location Cambridge Salary: circa £60k - £80k + Bonus + generous benefits Vacancy Location: Cambridgeshire (Commutable from Peterborough, Cambridge, Northampton, Bedford, St Neots, Stevenage, Milton Keynes, etc) For more about this opportunity please contact Adam Mayne () #J-18808-Ljbffr

Firmware Engineer – Cambridge Would you like to work on developing an extremely precise deep-tech platform with real-world impact? Our client offers the chance to work with a multidisciplinary team on cutting-edge technologies, alongside a motivated group of engineers. • Develop driver firmware for proprietary silicon, • Work throughout the whole SDLC, including bring-up, regression testing and performance testing, • Validate new silicon chips Experience required: • Strong background in real-time embedded firmware, • 5+ years of experience with C/C++ development, • 2+ years of experience with Python, • Experience developing cross-platform code Desirable skills: • Experience with unit test frameworks like pytest, build scripting, Jenkins CI/CD automation, • Good understanding of ARM Cortex-M series processors and CPU architecture, • Some PCB electronics design experiences, • Familiarity with Linux, Git, Bash, and Tcl, • Private health insurance, • Life insurance, • 33 days holiday, • Expert training from renowned industry veterans Apply now to join a company truly leading their niche in one of the most vibrant cities on Earth for R&D #J-18808-Ljbffr

Location: Cambridge In‑office expectation: Once every two weeks Employment type: Permanent Salary: £55,000-£75,000 This role will be a mid or senior level engineer dependant on experience Redgate's Foundry is our innovation incubator, the team scanning the horizon for Redgate's next big opportunity. This role exists because that kind of work needs engineers who are genuinely excited by discovery: people who can form a hypothesis, test it fast, and make a clear‑eyed call on whether to push forward or change course. Most ideas won't become products. That's by design. Each experiment sharpens our thinking and improves the odds of finding the one that will. If you're motivated by that kind of challenge, where the destination isn't fixed and the work is never the same twice, this is the role for you. Redgate brings together people who want to do their best work in an environment built on trust, accountability, and collaboration. We build solutions that help data professionals securely manage the data and databases that their organisations depend on, a space that's only becoming more critical as systems scale, data regulations increase, and AI adoption accelerates. • You’ll work in a team that cares about collaboration, craft and quality, not just in how we build, but in choosing what to build, finding the shortest path to the questions that matter most., • There’s real scope to grow your skills and impact, with clear pathways and support., • We value sustainable delivery, good ways of working and time to improve how we build. The Foundry operates differently to the rest of Redgate's product teams. You won't be handed a roadmap. Instead, you'll work across the full arc of innovation - from horizon-scanning and ideation through to early-stage research, rapid prototyping, and working directly with customers to validate what you're building. You’ll be part of a small cross-functional team (a Tech Lead plus four to six Software and Machine Learning Engineers), and you’ll regularly run projects in parallel: contributing to ongoing experiments while also exploring entirely new directions. The tech stack is deliberately varied, the right tool for the job, not a fixed list, spanning C#, TypeScript, Python, and more across desktop, web, API, database, and ML development. What makes this role different: • You’ll work on problems where there is no established answer and you’ll have the autonomy to explore them seriously., • Your work sits at the intersection of software engineering, customer insight, and product thinking; it’s rare to find all three in one role., • You’ll use and help shape how Redgate adopts agentic coding and AI development tools, not as an afterthought, but as a core part of how the team works., • The scope is genuinely broad: a typical day could see you balancing technical prototypes, customer interviews, and competitor teardowns., • Proven experience using AI coding tools. You’ve used them extensively, understand their limitations, and have developed ways to work around them productively and safely., • Strong software design and coding skills across modern languages, particularly C#, TypeScript, or Python, enough to guide and review AI‑generated code with confidence., • Hands‑on experience building agentic systems using frameworks such as LangGraph, Microsoft Agentic Framework, or MCP, with a solid understanding of LLM capabilities and risks., • Experience designing and running experiments to validate ideas quickly, using technical prototypes, customer feedback, and lean startup principles to test assumptions and make clear decisions., • Comfortable engaging directly with customers and stakeholders: running interviews, demos, and concierge‑style validation processes, and communicating findings clearly to both technical and non-technical audiences., • A product mindset; you think in terms of user value, outcomes, and market fit, not just features or technical delivery., • Salary range: £55,000-£75,000, • Hybrid working: home and Cambridge office, • Monthly wellbeing allowance and generous paid time off, • Genuine investment in learning, development, and career progression, • Private health insurance Your application will be reviewed by a person, we don’t use AI or automated tools to assess applications. Every profile is read by one of our Talent Partners. You’ll hear back within a few days, whether it’s a next step or a no, we aim to respond promptly so you're not left wondering. Our interview process is straightforward and consistent, you’ll find more detail on our typical hiring process below, so you know what's coming and why. We believe that people do their best work in an environment built on respect, fairness, and trust and that diverse perspectives lead to better outcomes. Redgate is an equal opportunity employer, and we make hiring decisions based on skill, potential, and alignment with our values. #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build simulation software that helps engineers and investors explore how AI systems would behave with different processors, memory systems, networks or serving strategies. Your work will help turn models and existing software into a practical framework for comparing design choices against realistic LLM workloads. You will develop and connect simulation components, making sure that changes in one part of a system have the appropriate consequences elsewhere. This means understanding unfamiliar code, designing clear interfaces and building software whose predictions can be investigated and tested against measurements. We aim to reuse and extend existing frameworks wherever they provide a sound foundation. We welcome depth in one or more relevant areas, including simulation, systems software, performance modelling and inference serving. Your initial focus will reflect your strengths and the components we choose to build on, with complementary expertise added as the team grows. • Develop and integrate simulation components that capture behaviour and interactions relevant to an AI infrastructure comparison, • Work with the technical lead and our partners to evaluate existing frameworks and software, extending and connecting useful components through clear interfaces, • Develop appropriate models of system state and resource use so that changes in one component have the appropriate consequences elsewhere, • Build reproducible simulation scenarios, diagnostic outputs and tests that expose incorrect assumptions, integration errors and unsupported cases, • Work with measurement and uncertainty colleagues to compare predictions with evidence, improve models and integrate calibration and uncertainty methods into the simulator, • Maintain reliable software, documentation and development workflows, using AI coding agents to support implementation and testing An example early project would be to bridge an existing simulator component with our workload models and measurement datasets, producing a reproducible comparison between predicted and measured performance over two systems. • Strong software engineering skills and evidence of building, debugging and maintaining substantial technical software, • Experience in one or more of: discrete-event simulation; computer architecture or performance modelling; distributed/HPC systems; inference runtimes and serving; memory or network modelling; integration of scientific software and heterogeneous components, • The ability to understand unfamiliar code, reason about interfaces and assess the suitability and maintenance costs of reusing, extending or building software, • A collaborative approach to testing assumptions and working with specialists in adjacent areas, • Practical experience using AI coding agents, with the judgement to check their output for correctness and maintainability Python, C++, Rust or other relevant systems or scientific programming experience can provide a route into the role. Familiarity with vLLM or SGLang, simulator frameworks, or hardware performance tools would be useful. Depth in a subset of these areas is sufficient; languages and frameworks will follow the engineering needs of the programme. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

RemoteStar is looking to hire Remote Tech Lead-Node.js on behalf of our client based in the UK with a fully remote work policy. The client building, the B2B marketplace for diamonds. They have their presence in London, Hong Kong, Amsterdam, and as well in Mumbai. The Remote Tech Lead-Node.js will be maintaining existing features, building new features, and actively taking part in setting the direction of the backend, whether that be code structure, data structure, or feature set. • Hands-on Technical Solutioning of product features., • Serve as a mentor on technical, architectural, design, and related problems., • Proactively identify technical weaknesses and recommend appropriate solutions., • Deployment of code, database migrations, and a thorough understanding of the impact of changes in the production environment., • Understanding and augmenting the system and application architecture as needed., • Perform Code Reviews and take ownership in releasing new features to production., • Report on & improve the output of your team, • Liaise with management and key stakeholders to ensure technical solutions meet business goals, • Experience with managing teams, • Excellent hands-on experience with Node.Js, Express.Js, and JavaScript., • Good understanding of asynchronous programming, callback, and closures., • Test-driven development and use of frameworks like Mocha, and Cypress., • Should be strong in the Postgres database., • Excellent Object Oriented Programming skills and ability to write modular, secure, scalable, and maintainable code, • Knowledge about AWS components (S3, EC2, Cloudfront, Redis Clusters, Postgres, etc.), • Experience with GraphQL APIs., • Lots of responsibility and room to grow, • Opportunity to join a fast-growing company at an early stage., • Fast-paced and multinational working environment #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Lead the engineering team building a simulation platform for AI inference systems. You will bring together realistic workloads, hardware models and physical measurements to predict system performance and make the uncertainty in those predictions explicit. The platform will help engineers and investors assess emerging AI infrastructure, understand design choices, and identify next experiments. You will turn scientific direction into an implementable architecture and delivery plan, help shape recruitment, and develop a team with complementary expertise across software, modelling, measurement and hardware. You will report to the SIL Scientific Director and line manage a group of engineers in the growing SIL team. Working closely with the Director of Engineering, you will provide daily technical leadership and help shape the team as we recruit. Technical judgement and the ability to bring people with you matter more than having held a particular management title in the past. • Own the simulator codebase, working closely with the Scientific Director, SIL on architectural decisions. Translate the programme's scientific goals into an achievable engineering roadmap, • Assess existing simulators, serving software and partner components; decide what to reuse, extend or build, and establish interfaces that make the pieces work together, • Shape recruitment, assess candidates, mentor colleagues and line-manage engineers, building complementary expertise across software, measurement, modelling and hardware, • Ensure simulator predictions are tested against physical measurements and realistic LLM workloads, with uncertainty made explicit to the people interpreting the results, • Establish engineering practices for maintainable software, testing, reproducible experiments and effective use of AI coding agents; review designs and results with the relevant specialists, • Contribute directly to implementation and debugging when engineering coverage is incomplete or a colleague needs support An example early project would be to lead a complete study from an investor's question through simulation and measured validation to a useful evidence report, while establishing the team and foundations for subsequent cases. • Substantial industrial engineering experience delivering complex software or hardware/software systems, with clear examples of technical decisions you have owned, • Depth in at least one of systems simulation, computer architecture, distributed or HPC systems, inference serving, or experimental performance engineering. Experience across more than one is especially valuable, • Evidence that you can lead people through difficult technical work, explain trade-offs and develop others. This may come from technical leadership and mentoring as well as formal management, • The judgement to turn high-level scientific direction into independent engineering decisions, and to recognise when wider input is needed, • Practical engineering ability to review code and designs, investigate failures and help colleagues resolve implementation difficulties, • Experience using AI coding agents, with the ability to assess their output and help colleagues use them effectively Experience connecting research prototypes to maintained engineering systems, collaborating with universities or technology suppliers, and comparing models with measurements would be valuable. We do not expect you to be the deepest specialist in every part of the programme. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid working, with Cambridge attendance agreed individually around collaboration and job need. We would like you to start as soon as practical and can be flexible for the right person. We value engineering quality and demonstrated leadership over a particular qualification or previous management title. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

We are looking for a Senior Developer / Tech Lead for a fast growing and profitable startup from Norway. This is a Fully Remote role. A small fun, very profitable ecommerce startup with turnover of 70 and 80 million kroner. You will be working directly with the CTO and Founders. As a Tech Lead / Senior Developer, you will be able to control solution architecture and technology choices, and play a central role in how the company develops. Systems consist of a self-developed e-commerce platform to handle several thousand orders every day. It is very important to have a rock-solid, simple and stable solutions for our many customers and employees. You will be our only developer and therefore play a very central role in the company. You will work closely with the CTO to set new courses and develop new features. In addition, you get a really good group of colleagues in different disciplines. • Bachelor's degree in Computer Science, Engineering, or related field., • Proficiency in frontend development using Next.js and Node.js., • Strong understanding of microservice architecture and experience with Java backend development., • Experience with NGINX configuration and administration., • Familiarity with Unix-based systems and server management tools (systemd, ssh, bash scripting)., • Knowledge of SEO best practices and techniques., • Experience working with databases, including HSQLDB and sqlite3., • Familiarity with Next.js pages router and dynamic routing concepts., • Good communication skills in both Norwegian and English., • Competitive salary, • Flexible work hours, • Remote work options, • Professional development opportunities, • Collaborative and innovative work environment #J-18808-Ljbffr

Redgate creates simple software to help data professionals get the most value out of any database. Our solutions solve complex database management challenges across the DevOps lifecycle, making life easier for IT leaders, development, and operations teams by increasing efficiency, reducing errors, and protecting business-critical data. The data community trusts Redgate to balance speed to market, team collaboration, and data protection. Find out more about us here: • Redgate Software – Culture, • RepVue As a Senior Software Engineer, you'll be part of a small, cross-functional team that typically includes a Tech Lead, Lead Software Engineer, Product Designer, Product Manager, and 4–5 software engineers. Beyond your immediate team, you'll benefit from the support of the Group Engineering Manager—who oversees delivery, people, and processes across the group—an architect who provides technical direction at the product level, and a coaching function to help you get unblocked. This Senior Software Engineer role is for one of the teams working on Redgate Monitor, our flagship monitoring solution. Redgate Monitor is a widely used tool that helps organisations proactively monitor, diagnose, and optimise their database environments. As part of the Monitor team, you’ll contribute to the ongoing evolution of a mature, high-impact product. You’ll have the opportunity to influence architectural decisions, improve system performance, and deliver features that directly benefit thousands of customers worldwide. As a Senior Software Engineer, you are expected to demonstrate both breadth and depth of technical expertise. You will confidently solve complex problems with clean, simple solutions, lead and contribute to large, challenging projects, and act as a technical influencer within your team. In addition to championing best practices, you will proactively drive improvements in processes, tooling, and architecture that benefit the wider engineering organisation. Beyond technical skills, a key part of the senior role is elevating others. This includes mentoring, coaching, teaching, and sharing your expertise through conversations, documentation, and technical talks. You act as a force multiplier, raising the technical abilities of your teammates and improving the engineering environment for all. With a growth mindset, you will actively foster a culture of continuous learning, collaboration, and psychological safety. • Designing, building and testing world‑class software, with a focus on scalable, resilient, and secure systems., • Providing guidance and direction to the team when faced with software design and implementation challenges, owning the toughest and most ambiguous technical problems., • Writing well‑tested code and maintaining high standards for code quality, system design, and testing., • Taking part in reviews of your own and other developers’ code, offering specific, actionable feedback on code, designs, and behaviours that helps others., • Collaborating with the team to ensure the product is of high quality., • Working closely with the user experience specialists to design, implement and improve the product’s user experience., • Working closely with the team to ensure the product is supported by solid technical documentation, and API specifications., • Identifying tools and techniques to improve software engineering, sharing these with the rest of Redgate and beyond., • Building strong relationships with stakeholders, fostering a positive environment., • Understanding how the product or systems owned by your team solve customer problems and add value, prioritising engineering work based on its potential to provide value to customers., • Taking ownership of significant projects from start to finish, ensuring delivery of tangible business value through strategic planning and predictable execution., • You actively engage with users to understand how the product is used in the real world and bring customer empathy into your engineering decisions., • You’re an expert in modern .NET/ C#., • You can design and build scalable, resilient, and secure systems, considering trade‑offs and future implications., • You have a bias for simplicity and maintainability in the code you write and the products you build., • You practice unit testing, perform code reviews and constantly communicate to ensure the best outcome. Quality is important to you., • You’re an excellent communicator with good attention to detail, able to communicate effectively both in person and in writing., • You thrive in a highly collaborative team, building strong relationships and fostering a positive environment., • You’re flexible and willing to work on all parts of the product, learning new technologies as necessary., • You have superb software design skills., • You have experience in an agile development environment., • You’re enthusiastic about engaging with customers as necessary to create a great product., • You are driven by continuous improvement and foster a growth mindset within the team., • You have experience working with SQL Server, PostgreSQL, or Oracle., • You have experience developing applications using React., • You have experience working with Agile, Lean and/or Continuous Delivery approaches and best practices, such as Continuous Integration, TDD, BDD, Infrastructure as Code etc. We believe diverse teams are better at solving problems and fostering a creative culture. We aim to offer a workplace where everyone feels a sense of belonging and can thrive. • Recruitment & retention: hiring and retaining diverse talent., • Authenticity & belonging: promoting inclusive language and behaviours., • Growth: supporting personal and professional development. We support DEIB through our inclusion forum (Belong at Redgate) and regular DEIB events. Redgate is an equal opportunity employer, welcoming applications from all backgrounds. If you need accommodation, please let us know via our application process or email . Learn more about our commitment to diversity on our diversity page. While we outline the qualities we typically seek, we recognise that you may possess additional attributes and skills that could make you an excellent fit for our team. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #J-18808-Ljbffr

Immigration Partner – Cambridge or Thames Valley. We are looking for an ambitious and commercially minded Immigration Solicitor to join us at Partner level, to lead the next phase of growth for our large immigration practice. Part of our nationally recognised Employment, Immigration and HR team, this is an exciting opportunity for an established lawyer to shape, expand and build upon our successful immigration offering. Our immigration experts provide support for both business and personal immigration matters for senior executives and high-net worth private clients. Our immigration team is one of the largest outside of London and is known for providing pragmatic, commercial advice to clients across a range of sectors. Our clients rely on us to help them navigate complex immigration requirements, from sponsor licence applications and compliance through to strategic workforce planning and global mobility solutions. This role offers the platform, investment, and cross-referral opportunities to build a substantial practice within a collaborative and entrepreneurial firm. As a senior leader within the team, you will play a pivotal role in driving the continued growth of our immigration offering. Working alongside partners across the firm, you will identify opportunities, strengthen existing client relationships, and develop new sources of work. We are particularly interested in speaking with individuals who bring strong market connections, a proven track record of business and a genuine appetite for growing. • Be a part of leading and shaping our national immigration practice., • Advise employers, education clients and other organisations on complex immigration and compliance., • Support clients with sponsor licences, workforce planning, global mobility issues, compliance audits, and Home Office investigations., • Develop new business opportunities and enhance existing client relationships., • Build your profile in the market through networking, speaking engagements and thought leadership., • Mentor and develop lawyers within the wider team., • Contribute to the strategic direction of the practice and wider firm. You will be an established Immigration Partner, Legal Director or Senior Immigration Lawyer with – • Significant experience advising businesses on complex UK immigration matters. You’ll have atleast 7 years PQE., • A strong reputation within the market and an established network of contacts or a credible business case for developing one., • A track record of winning, retaining and growing client relationships., • Have a proven track‑record of supporting clients in the tech and manufacturing industries., • Excellent technical expertise and commercial awareness., • A collaborative approach and commitment to mentoring and developing others. With strong referral streams across the firm, an established client base and ambitious growth plans, this is an opportunity to join a highly collaborative partnership and build something significant. For the right individual, this role is an opportunity to join a successful practice and be instrumental in shaping its future growth. • Income, • Protection, • Private MedicalInsurance, • Sight tests / Glasses discounts, • Car Loans, • Scottish Widows Pension Scheme, • 28 days annual leave (plus public holidays), • Bonus scheme, • Electric vehicle scheme, • Happy People / Perks at Work benefits portal, • Cycle to Work scheme, • Life Assurance, • 1/3 gym membership contribution, • Flu vaccinations HCR suits people who love a challenge and want to work in an environment where careers thrive on the back of hard work and personal merit. Our people enjoy feeling part of something bigger than themselves, and whilst our clients drive our development, it is our people who bring their energy, enthusiasm, and entrepreneurial mindsets together to solve problems and help our clients succeed. Our people tell us they enjoy working on good quality, interesting matters from a wide variety of our clients, because they get the experience they want to develop their careers. We will give you responsibility early, the mandate to make things happen and we’ll back your good ideas. Our “Passion for People” lives and breathes every day throughout the firm as our peoples’ energy and sense of fun create a warm environment in which to thrive. HCR’s growth constantly creates opportunities for people who want to go places and make a difference, your career plan can become part of our growth plan. At HCR you can expect to work with friendly, energetic, ambitious people, who love getting stuck into a client problem, and enjoy celebrating a good outcome. Our people value the sense of community provided by the individual personality of each office and the collegiate approach across all our service and sector teams. As a Times Best Law firm, among the UK Top 50, we provide the full range of services that you would expect to organisations, business leaders and individuals. However, in our mission to give everyone the opportunity to experience a different kind of legal service we take an entrepreneurial approach. We’re flexible and responsive to the needs of our clients, delivering the best outcomes for them. We have more than 1000 lawyers and support staff, including more than 180 partners, and have been awarded the Law Society’s Lexcel quality mark in recognition of our compliance and client care standards. With 13 offices in England and Wales our well-established presence stretches from west to east, ensuring clients can access a full-service legal offering no matter where they’re located. We’ve expanded significantly across all our regions, and are well-respected as a regional firm with a strong London and international presence. With solid connections in the communities we work in, and a track record of delivering legal advice to businesses and individuals throughout the areas we base ourselves in, our clients continue to value our approach to providing legal advice, in the way they need, when they need it. As HCR is an equal opportunities employer, we don’t just accept differences, we celebrate them. We want to attract a diverse and ambitious workforce that reflects all backgrounds and skills to create a workplace that is supportive and inclusive, recognises and nurtures talent, and which works together to achieve the best outcome for our clients. We are privileged to be an armed forces-friendly organisation. #J-18808-Ljbffr

CommonAI CIC is redefining deep-tech AI solutions through collaborative engineering and shared infrastructure. Working at the intersection of AI, cloud and large-scale infrastructure, we partner with commercial, government and research entities to accelerate AI adoption across the UK and Europe. Backed by UK Government and private funding, our team of experienced founders and engineers is building the future of AI systems. Its members include ARIA, Barclays and a fast-growing group of deeptech startups. Highly regulated industries like financial services need guaranteed, predictable outcomes that today's large language models cannot provide on their own. Our High Assurance programme will develop AI systems which can be used safely in environments where accuracy and explainability are critical building blocks in creating a required level of trust. • Formal methods and verification: proofs that an AI system must satisfy before it can act., • Domain-specific small language models for regulated use cases., • AI control platforms that govern how AI systems behave in production. The programme launched recently, with Barclays as its lead member and held its first workshop, "Towards Trustworthy Harnesses", with members, academics and domain experts. We are looking for a Programme Technical Lead to drive execution of the High Assurance AI Programme. The programme already has an academic architectural lead; this role turns the programme's research direction into delivered engineering, working closely with the architectural lead, our Chief Science Officer and our members. You will report to the CTO and build and lead the programme's engineering team. • Own delivery of the programme's technical roadmap, from research direction to working infrastructure., • Build, hire and lead an engineering team based in Cambridge., • Translate the needs of regulated industries into clear technical requirements, making sure the programme solves the problems which matter to members., • Bring members, researchers and partners together around a shared roadmap., • Work with the architectural lead to evaluate approaches such as formal methods, AI control and small language models and decide what to build., • Represent the programme technically with members and partners. We do not expect anyone to have all of the experience below. Deep expertise in one area, combined with the ability to work across the others, matters more than ticking every box. • Understanding/experience of processes/workflows (and their associated constraints) in the financial services industry, particularly banks., • Understanding of how AI is or might be used, governed or assured in a regulated industry, ideally financial services (for example model risk, AI governance or controls)., • Experience with PyTorch or other similar frameworks., • Enough technical depth to engage credibly with ML researchers and understand the problems the programme needs to solve, without needing to be the person who writes the proofs or algorithms., • Ability to bring together organisations with different priorities and build a shared plan., • Experience leading an engineering team and driving delivery in a technical, research-driven environment., • Experience with formal methods, verification, AI safety, AI assurance or AI control., • Experience with small or domain-specific language models., • Relationships with banks, insurers or regulators., • Experience in a startup, or building a new product, or independent project / research that has resulted in software used by others. Lead a new programme at the boundary of research and industry, helping to solve tough challenges such as how AI can be used safely in critical industries. High-impact role in a rapidly growing, well-funded organisation. Mission-led work for the public good, released over time as managed open source. • Competitive salary, pension, healthcare and benefits, including company share scheme., • Networking opportunities with leaders across tech and academia., • Vibrant office situated near to Cambridge train station. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Our world-leading semiconductor client has an exciting opportunity for a Staff Analog IC Design Engineer with data converter experience to join their Cambridge team developing 5G IoT radio technology. As Staff Analog IC Design Engineer you will work on advanced wireless systems and enjoy good compensation, smart peers, and have a real product impact. Working on a wide range of circuits with an emphasis on low power design, you will drive design from initial architecture through to final delivery of design and enjoy plenty of scope to innovate new techniques to cater for challenging circuit requirements. The successful candidate will have a solid background within Analog IC Design and ADCs/DACs. Essentials include: • A BSc / MSc in Electronic Engineering or similar field, • Established industrial experience within analog IC design, • A solid background in ADC/DAC design, • Proficiency in Cadence Virtuoso, • Experience with advanced process technologies (22nm, 14nm, 6nm) You can expect a solid package that includes competitive salary, pension, private healthcare, annual bonus and many other company perks. Join one of the world’s tech leaders and take the next step in your career! #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Design and run experiments that reveal how AI infrastructure behaves, what limits its performance and how reliably that behaviour can be predicted. You will build measurement tools and turn observations of real hardware and software into evidence for SIL's simulation platform and the investment decisions it supports. Your work will range from targeted experiments on individual components to measurements of complete LLM serving systems. Working with workload, simulation and uncertainty specialists, you will investigate bottlenecks, explain performance variation and identify the meaningful effects. We welcome deep expertise in one or more parts of the hardware and software stack. You will work with colleagues who bring complementary strengths, with scope to broaden your expertise as the team grows. • Design and run reproducible experiments, from individual hardware or software components to complete LLM serving systems, covering relevant workloads, configurations and operating conditions, • Develop reusable measurement tools and collect traces, profiles and counters to characterise latency, throughput, memory behaviour and, where reliable measurement is possible, power and energy, • Investigate bottlenecks, performance variation and unexpected behaviour across the layers your expertise covers, working with colleagues to extend the investigation through the stack, • Take responsibility for reproducible workload details, software versions, configuration and measurement methods so results can be reproduced, compared and used to calibrate simulator models, • Work with simulation and uncertainty specialists to choose measurements that resolve important unknowns and undertake curation of calibration and validation data, • Help define the controls needed for experiments and use the resulting cluster-control interfaces, coordinating access and changes with colleagues responsible for the hardware An example early project would be to work with workload colleagues to establish a reproducible reference experiment and measurement dataset, investigating how performance changes under a selected configuration or load change. • Experience investigating the performance of real computing systems and designing experiments that support rigorous conclusions, • Depth in one or more relevant areas: accelerator profiling, inference runtimes, memory systems, distributed/HPC workloads, networking, or power and energy measurement, • The ability to build maintainable automation and analysis tools in a suitable software language, and to learn unfamiliar profiling tools, • Knowledge and care of experimental controls, repeatability, confounding effects and the limits of a measurement, • Some experience using AI coding agents, alongside sound debugging and review habits LLM serving experience and familiarity with tools such as Nsight, PyTorch Profiler or system/network profilers would be useful. These are examples, not a requirement to know every tool. Strong expertise in one part of the stack is welcome; we can shape the role and recruit complementary strengths around it. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part‑time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier‑career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. #J-18808-Ljbffr

This is a fantastic opportunity to join Luminance, the pioneer of Legal-Grade™ AI for enterprise. Backed by internationally renowned VCs and named in both the Forbes AI 50 list of ‘Most Promising Private AI Companies in the World’ and Inc. 5000’s ‘Fastest Growing Companies in America’, Luminance is disrupting the legal profession around the globe. As a Delivery Engineer, you are responsible for the software development lifecycle (SLDC) that results in packaged releases of Luminance software that can be distributed to our client base. During your day-to-day you will ensure that the lifecycle runs efficiently and to a high standard, driving processes forward to help meet commercial goals and adding assistance and guidance to the tech team when you come across inefficiencies or bottlenecks. Your long-term responsibilities are to analyse the SDLC for weak points and propose or build human and/or automation solutions that provide long term benefit to the efficiency, reliability and visibility of the SDLC. If you are excited about this role but your skill or experience doesn’t perfectly align with the job description, we encourage you to apply anyway. At Luminance we are dedicated to building and promoting an inclusive workplace where everyone can flourish. You might just be who we’re looking for, for this role or another – enthusiasm is by far the most important requirement for any applicant to Luminance! • Technically highly proficient, • Can build if required, but more importantly you know what good looks like and are able to direct other teams as a result, • Teamwork:, • Breadth of operation, • Highly empathetic to different teams' needs, • Understanding of Luminance people and product, • Communication:, • Can organise and simplify information and summarise/translate to different stakeholders, • Calm under pressure, • Customer focused, • Confident/Self-Belief/Assertive when right, • Project Management, • Pragmatism - the ability to balance delivery vs quality pressures, • Strong work ethic, • A sense of urgency in their work, • Happy to get stuck into something and find out all the details, • Reliable - will follow something through to completion and not be satisfied until it is, • Adaptable - can learn quickly on the fly to facilitate good decision making #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Make uncertainty a first-class output of an AI systems simulator. When a simulation predicts that one design will outperform another, you will help establish how much confidence the evidence supports, which assumptions could change the conclusion, and which experiments would reduce the uncertainty that matters to the decision. You will combine mathematical reasoning with practical software engineering to calibrate models against measurements, test predictions on independent cases and build uncertainty analysis into the simulation workflow. Your methods and software will help engineers and investors understand what the simulator predicts and the limits of those predictions. We welcome people from AI systems, HPC and other fields where simulation is tested against experiments. You might bring systems engineering experience and an interest in developing uncertainty methods, or experience in mathematical modelling and scientific computing that you want to apply to AI infrastructure. • Develop and implement methods to calibrate simulator models against measurements and evaluate predictions on cases that were not used for calibration, • Distinguish uncertainty arising from measurements, model assumptions and parameters, operational variation and limited simulation runs, and represent it appropriately, • Analyse sensitivity and uncertainty in comparisons between alternatives, accounting for shared sources of uncertainty and their effects on the comparison, • Develop outputs that show how uncertain a prediction is, when a ranking could change, and when a result extends beyond the evidence used to validate it, • Work with measurement and workload engineers to design experiments that test modelling assumptions and reduce uncertainty that matters to the decision, • Integrate these methods into repeatable simulation workflows and communicate their assumptions and limitations to engineers and the technical analyst An example early project might be to establish a calibration and validation workflow for the a comparison between two architectures, with uncertainty outputs that help explain the result. You will develop and review the methodology with the technical lead and Scientific Director, SIL. • Mathematical maturity: the ability to reason carefully about models, data, variation and the assumptions behind a quantitative claim, • Software engineering experience sufficient to turn numerical methods or analysis into readable, tested, reusable tools, • Relevant experience in one or more of: quantitative systems performance analysis, statistical modelling, simulation validation, uncertainty quantification, scientific/HPC software or the theory of experimental design, • The ability to collaborate with specialists and explain both a result and the limits of the evidence supporting it, • Practical experience using AI coding agents and checking their output Experience with model discrepancy, sensitivity analysis, Bayesian methods, surrogate models or sequential experimental design would be useful. So would familiarity with computer architecture or inference systems. We welcome complementary backgrounds: strong systems engineers developing uncertainty expertise, and engineers with modelling or uncertainty expertise moving into AI infrastructure. • Help build UK AI capability and improve how investment and compute serve the public good, • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities, • Shape a growing team with startup pace and close academic links, • Use frontier models and coding agents with a substantial tooling budget, • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

About CommonAI CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. The Opportunity Build the software that lets SIL configure and control real AI infrastructure for reproducible experiments. You will turn the capabilities of our experimental clusters into programmatic controls for changes such as workload placement, resource allocation and inference-serving configuration. The engineering challenge is making those changes dependable: understanding the current state, checking whether an action can be carried out, confirming what actually happened and handling failures. Your software will make it possible to repeat experiments and understand which configuration produced a result. Working with measurement and simulation engineers and cluster operators, you will establish useful controls for the first experimental studies. Those interfaces will also provide the actions that future design-space optimisation software can call. What you will do • Identify the controls available on the selected clusters and expose them through documented, programmatic interfaces with clear supported actions., • Automate configuration and experiment setup across relevant parts of the stack, such as workload placement, serving settings, resource allocation or device configuration., • Build reliable execution with precondition checks, confirmation of the resulting state, error handling and recovery to a known configuration where supported., • Record requested actions, outcomes and resulting configuration so experiments can be reproduced and measurements interpreted correctly., • Coordinate access, permissions and changes with cluster operators, and test success, failure and recovery paths within an agreed experimental scope., • Design interfaces that future optimisation software can call, with clear capability limits and explicit outcomes when an action cannot be completed. An example early project would be to build an interface for changing serving configurations and demonstrate a repeatable experiment across two configurations, including checks of the applied settings and recovery from a failed change. • Experience building systems software or automation that configures and controls real computing infrastructure., • Strong programming and debugging skills, with practical understanding of Linux and the relevant hardware/software interfaces., • Depth in one or more of: cluster or HPC automation, distributed systems, orchestration, device control, networking, or experiment-control software., • The ability to reason about partial failure, state, permissions and the consequences of changing a running system., • Practical experience using AI coding agents, with the judgement to validate generated code and test changes that affect hardware or infrastructure. Experience with accelerators, job-control systems, Kubernetes, Slurm, operating systems (NixOS, CoreOS) or IaC tools (Terraform/OpenTofu) would be useful. Depth in a subset is sufficient; the initial controls and integration choices will follow the needs and capabilities of SIL's clusters. Why join us • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes’ walk away from Cambridge train station Working with us Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

About CommonAI CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Build the software that lets SIL configure and control real AI infrastructure for reproducible experiments. You will turn the capabilities of our experimental clusters into programmatic controls for changes such as workload placement, resource allocation and inference-serving configuration. The engineering challenge is making those changes dependable: understanding the current state, checking whether an action can be carried out, confirming what actually happened and handling failures. Your software will make it possible to repeat experiments and understand which configuration produced a result. Working with measurement and simulation engineers and cluster operators, you will establish useful controls for the first experimental studies. Those interfaces will also provide the actions that future design-space optimisation software can call. • Identify the controls available on the selected clusters and expose them through documented, programmatic interfaces with clear supported actions., • Automate configuration and experiment setup across relevant parts of the stack, such as workload placement, serving settings, resource allocation or device configuration., • Build reliable execution with precondition checks, confirmation of the resulting state, error handling and recovery to a known configuration where supported., • Record requested actions, outcomes and resulting configuration so experiments can be reproduced and measurements interpreted correctly., • Coordinate access, permissions and changes with cluster operators, and test success, failure and recovery paths within an agreed experimental scope., • Design interfaces that future optimisation software can call, with clear capability limits and explicit outcomes when an action cannot be completed., • An example early project would be to build an interface for changing serving configurations and demonstrate a repeatable experiment across two configurations, including checks of the applied settings and recovery from a failed change., • Experience building systems software or automation that configures and controls real computing infrastructure., • Strong programming and debugging skills, with practical understanding of Linux and the relevant hardware/software interfaces., • Depth in one or more of: cluster or HPC automation, distributed systems, orchestration, device control, networking, or experiment-control software., • The ability to reason about partial failure, state, permissions and the consequences of changing a running system., • Practical experience using AI coding agents, with the judgement to validate generated code and test changes that affect hardware or infrastructure. Experience with accelerators, job-control systems, Kubernetes, Slurm, operating systems (NixOS, CoreOS) or IaC tools (Terraform/OpenTofu) would be useful., • Depth in a subset is sufficient; the initial controls and integration choices will follow the needs and capabilities of SIL's clusters., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with regular time in Cambridge agreed individually around hardware work and collaboration; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers but will also consider earlier‑career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Cambridge, UK Graphcoreis one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group,Graphcoreis a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives.A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties • Developing ourinternal toolingforbuilding,testingand integrating togetherthe ML Software Stack, • Developing tools and technical processes for Software Releases, • Providing guidanceto developersonbestbuildpracticesand dependency management, • Communicatingregularly withdevelopers,tech leads,andsoftwarearchitectsaboutaspects of the MLSoftware Stack, • Working closely with QA and the ML Software Stack to resolve any integration issues, • Contributing fixes towards the ML Software Stack, • Knowledge of Python/C++ (or similar language), • UnderstandingofBuildProcesses andFrameworks, • Experience working in Linux environments, • Good communicationskills, • Experience withRemoteCaching andExecution(e.g. Bazel), • Experience withBuild Tools(e.g.CMake), • Experience with Testing Frameworks (e.g.PyTest,GoogleTest), • Experience with Integration Tools (e.g.Buildstream), • Experience working within the Software Development Lifecycle (SDLC), • Experience with building and using containers (e.g. Docker,Podman), • An understanding of Software Architecture patterns In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications #J-18808-Ljbffr

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. Make uncertainty a first-class output of an AI systems simulator. When a simulation predicts that one design will outperform another, you will help establish how much confidence the evidence supports, which assumptions could change the conclusion, and which experiments would reduce the uncertainty that matters to the decision. You will combine mathematical reasoning with practical software engineering to calibrate models against measurements, test predictions on independent cases and build uncertainty analysis into the simulation workflow. Your methods and software will help engineers and investors understand what the simulator predicts and the limits of those predictions. We welcome people from AI systems, HPC and other fields where simulation is tested against experiments. You might bring systems engineering experience and an interest in developing uncertainty methods, or experience in mathematical modelling and scientific computing that you want to apply to AI infrastructure. • Develop and implement methods to calibrate simulator models against measurements and evaluate predictions on cases that were not used for calibration., • Distinguish uncertainty arising from measurements, model assumptions and parameters, operational variation and limited simulation runs, and represent it appropriately., • Analyse sensitivity and uncertainty in comparisons between alternatives, accounting for shared sources of uncertainty and their effects on the comparison., • Develop outputs that show how uncertain a prediction is, when a ranking could change, and when a result extends beyond the evidence used to validate it., • Work with measurement and workload engineers to design experiments that test modelling assumptions and reduce uncertainty that matters to the decision., • Integrate these methods into repeatable simulation workflows and communicate their assumptions and limitations to engineers and the technical analyst. An example early project might be to establish a calibration and validation workflow for the a comparison between two architectures, with uncertainty outputs that help explain the result. You will develop and review the methodology with the technical lead and Scientific Director, SIL. • Mathematical maturity: the ability to reason carefully about models, data, variation and the assumptions behind a quantitative claim., • Software engineering experience sufficient to turn numerical methods or analysis into readable, tested, reusable tools., • Relevant experience in one or more of: quantitative systems performance analysis, statistical modelling, simulation validation, uncertainty quantification, scientific/HPC software or the theory of experimental design., • The ability to collaborate with specialists and explain both a result and the limits of the evidence supporting it., • Practical experience using AI coding agents and checking their output. Experience with model discrepancy, sensitivity analysis, Bayesian methods, surrogate models or sequential experimental design would be useful. So would familiarity with computer architecture or inference systems. We welcome complementary backgrounds: strong systems engineers developing uncertainty expertise, and engineers with modelling or uncertainty expertise moving into AI infrastructure. • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget., • A collaborative and supportive work environment, • The opportunity to have a high impact in a growing organisation, • Competitive salary package, including pension and benefits, • Professional development opportunities, • Networking opportunities with influential figures from across the tech sector and academia, • A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier-career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Here at Sepura, the NPI Engineer is involved in the whole lifecycle of product development from concept and prototype stages, through to production and support. As NPI Engineer, you will have a strong background in DFMA, transferring products from development to key production processes such as PCBA, Final Assembly and final pack-out. Experience working with Contract Manufacturers to introduce new products & processes, is a key requirement. Come and join Sepura Ltd at an exciting time of growth and progress your career within this innovative technology company, based in Waterbeach, Cambridge. • Responsible for the transfer and introduction of new product developments to the supply chain., • Working within the development team, you’ll take the lead to ensure that the supply chain and sub-contract manufacturers are prepared to produce in high volume and at the correct level of quality., • Developing & implementing new manufacturing equipment and processes and ensuring they are documented and qualified to meet yield and capacity targets., • Defining rules for Design for Manufacture and Assembly - confirming that the PCB & Mechanical designs are appropriate for the manufacturing techniques and cost effective., • Managing prototype builds (ensuring logistics of key parts are in control, build plans are in place, production lines are prepared & any issues are recorded)., • Supporting root cause analysis of prototype build issues down to mechanical product design or assembly issues and suggesting / implementing corrective actions., • Providing on-going support to our production partners to address any process / design issues which arise after mass production ramp., • Creation and or review of supplier work instructions (ensuring that the suppliers have appropriate documentation regarding their assembly and test process, and that the documentation is acceptable)., • Ensuring all Sepura operations teams are prepared for the introduction of the new product (e.g. Service and Repair, Customisation, Stores, etc.). Our customer base includes many different industries and markets around the world. Our complete TETRA and LTE solutions have been developed specifically for users in multiple sectors to face their critical communications challenges. There is no such thing as a typical day here at Sepura. You will be supported by your manager and team, as well as collaborating with other departments across the business. NPI Engineering activities you will be responsible for include: • NPI / Manufacturing / Production / Process Engineering, across a wide array of electro-mechanical products., • Managing end to end NPI process, from project concept though to production ramp., • Developing electro-mechanical production processes such as SMT & electro-mechanical assembly., • Applying process knowledge to root cause issues found during product assembly and test., • Regularly communication to both technical and non-technical personnel using verbal and written styles., • Enthusiastic, communicative and inquisitive., • Motivated by delivering quality work within planned timescales., • A structured, proactive approach - numerically focused., • Customer (internal and external) focused., • Commercially aware., • Creative yet detail focused, • Calm under pressure, • Ambitious, • Flexible, • Enthusiastic, • Self-motivated This job involves travel some of which is overseas. Therefore, candidates must have a valid drivers licence, own car and a valid passport. Travel expenses will be paid. • Travel expenses will be paid. What you need to succeed • A good academic record including higher education (HNC / Bachelor’s Degree) in a scientific or engineering related subject., • Otherwise, demonstration of significant relevant experience in a similar Engineering role., • Six Sigma, • Statistical Process Control, • DFM, • NPI / Manufacturing / Production / Process Engineer with proven electro-mechanical product manufacturing experience., • Sound experience of end-to-end NPI process, from project concept though to production ramp., • Good understanding of electro-mechanical production processes such as SMT & electro-mechanical assembly., • Experience in data analysis of high volume product assembly and test yields., • Planning and co-ordination of NPI deliverable tasks to align with wider Project schedule., • Experience of working with electronics contract manufacturers., • Knowledge of low-cost manufacturing techniques., • Basic knowledge of Injection Moulding process and or aluminium casting processes., • Experience of working in a medium size ‘high tech’ company., • Good Project planning & co-ordination., • Experience of working with formal PLM systems (Oracle Agile). #J-18808-Ljbffr

Hi 👋 I’m Colin, Director of Engineering, Europe. How do you feel about engineers writing product specs, making product decisions, and not breaking down projects into individual tickets? If that sounds exciting (even if a bit scary), read on because I’m looking for an engineering manager to help us build a different type of engineering team and culture at Ashby. To start, why do we need to be different? Time and again, I have witnessed engineers knowing what needs to be done yet being unable to get things done because of “the process” or because “more data is needed.” Some of the most effective projects have been skunkworks projects, where engineers have taken total ownership of a problem and driven it to completion. I want to normalize that at Ashby. When we think about how these processes came about, we realize they carry a pessimistic mindset. They box people into smaller roles to minimize the chance of not meeting a certain standard. At Ashby. we’re building an environment that is optimistic about what engineers can own and achieve and embraces the innovative engineers (and frankly, often stays out of their way). To accomplish this, our engineering leaders need to think deeply about individual performance, process, and culture - not running sprint planning or driving product and technical decisions. You’ll focus on building your team, their skills to thrive with the ownership they’re given, and an environment that empowers them to do their best work consistently, with little distraction. For junior EMs we try to stay within 6 direct reports. This enables them to spend time with our teams observing, correcting, praising, and, yes, coding. We like our managers to be hands‑on while also making sure they’re not on the critical path. We’ve already gathered an experienced, talented, and collaborative team of 25+ engineers. You’ll help me manage the growing team of engineers in Europe. • Provide feedback on product and technical specs to help engineers identify where to cut scope or improve quality. You don’t make the final decisions, but you’ll influence and coach ICs to reach the right ones., • Grow engineers to the point where they can take large, loosely defined projects, and deliver them with little intervention. They still ask for help when needed - the difference is that they’re driving., • Jump into our systems and code to debug a customer issue, ship a small bug fix, or improve our developer experience. Engineering leaders at Ashby are great engineers and enjoy keeping their skills up-to-date (while staying off the critical path)., • Improve how we generate and simulate data in demo accounts. It’s a project off the critical path, but it helps you keep up‑to‑date on our codebase while immensely impacting the business, from Engineering to QA to Sales. I had two experiences early in my career that set me on my path. I had a great manager who asked tonnes of questions about the decisions I was making and coached me without me realizing it. And I had a terrible manager - being told to work harder after a week of 3am finishes was not what I needed as a young engineer. The stark difference between these two experiences motivated me to become a manager: I wanted every engineer I worked with to have the support I had in the best case. Since then, as I’ve learned more, I’ve realized that I love the kind of problems I get to solve as a manager. Deeply complex problems with long-term impact both on the company and on people’s lives. One of my proudest achievements is creating a fully transparent pay system, and on the day it was revealed, everybody was happy with it. Nobody stormed out. By spending time thinking deeply about everybody’s pay and ensuring the mechanics of promotion were clear, I put the team in a place where they could see a peer was paid more than them and it not be a problem. Despite all this, I love being technical. I sometimes indulge myself and spend a morning writing some code to improve tests or provide better abstractions. If I couldn’t be a manager, I’d be super happy to be an IC. I’m looking for someone who is passionate. Passionate about both management and being technical. Someone who spots a pattern amongst their team, figures out a better way for us to operate, and then builds the automation that powers it. I introduced a new process that enables engineers to merge 30% of PRs without a human review beforehand. I also built the automation that approves these PRs. I also built that automation with abstractions that make it easy for the engineers to improve the automation themselves. It can be hard to find seasoned engineering leaders who haven’t succumbed to the status quo in some way or another. We’re committed to giving all our people a total and utter lack of terrible managers, and that means we’re willing to take a chance on someone early in their leadership journey who’s courageous, principled, and has the drive to build themselves into a great leader who can say “Yah I know everyone is doing that, but we won’t because…” Engineering Leadership Comes In Many Flavors, Not All Of Which Fit Our Model. I Thought I’d Outline Some Things I’m Looking For To Help You Decide If This Fits What You’re Looking For • You love being technical and can hold in-depth conversations with direct reports from infra to backend to frontend., • You enjoy management problems. We want people who get excited about driving people to be their best, giving difficult feedback, and building systems that make this easier., • You hold your team to a high standard and don’t shy away from getting into the details and giving feedback, even to the best folks on your team., • You are an excellent and empathetic communicator. Facilitating change at both an individual and organization level requires understanding how to navigate the beliefs, opinions, and past experiences of engineers and figuring out how to both convince them of a new way of doing things while also leaving yourself open to feedback., • You know what exceptional engineers look like. You’ve thought deeply about what makes them tick, how to recruit them, and how to grow folks into them. I want to see depth here, the industry often regurgitates a vanilla description, but the reality is more nuanced., • You’re good at thinking about product, business, and maybe even design, but you’re not interested in calling the shots and are more interested in building a team that can make the best decisions without you., • You thrive in high-trust, high-autonomy environments. We’re a young startup where leaders wear multiple hats, and you’ll build your own (high-speed) on-ramp through developing strong feedback loops., • You don’t enjoy coding or don’t find time to stay up-to-date on technology., • You’ve gotten into management because it was the only growth path available., • You want to make all the product decisions instead of empowering your team to make those calls., • You’re happy with a team of engineers that are predominantly early-career, mid-career, or don’t thrive with ownership or autonomy. With enough guardrails, the team can get things done., • A staff or principal engineer to you is someone who spends most of their time project managing or doing architecture reviews., • You’re not optimistic or convinced that we can build a large engineering team that functions differently than the status quo. You think, at some size, common processes need to be implemented to ensure consistent product delivery (e.g., sprint planning, product managers writing in-depth specifications). You might not say it out loud, but you think, at some size, compromises have to be made for the sake of hiring numbers. Talent teams aspire to build a hiring process that identifies great candidates, moves them quickly through the interview process, and provides an excellent experience for the candidate. To accomplish this, recruiters perform thousands of daily tasks to coordinate and relay information between candidates, interviewers, and hiring managers. Teams struggle to keep up! Scheduling a final round is an excellent example of our customers' challenges. A recruiter needs to collect availability from the candidate, identify potential interviewers, perform “Calendar Tetris” to find who is available to interview the candidate, schedule on the earliest date possible, and perform any last-minute adjustments as availability changes. They must perform this while considering the interview load on each individual and whether interviewers need to be trained and shadowing others. Ashby provides talent teams with intelligent and powerful software that provides insights into where they’re failing and automates or simplifies many of the tasks they’re underwater with. We put a lot of effort into designing products that are approachable to beginners but mastered and extended by power users. In many ways, spreadsheets set the bar here. We have many customers, great revenue growth, years of runway, and amazing investors like YCombinator, Elad Gil, and Lachy Groom. I’ll share more once we meet. Our engineering culture is motivated by Abhik and Benji’s (our co‑founders) belief that a small talented team, given the right environment, can build high‑quality software fast (and work regular hours!). Our engineering team (and the team at large) consists of lifelong learners who are humble and kind (meet them here!). These attributes create an environment where collaboration happens naturally (we filter for it in interviews). We combine this with research, prototyping, and written proposals to see around corners and get feedback from the team across time zones. Focus time is something that we hold sacred, and, with thoughtful and deliberate communication, engineers can focus 36h out of a 40h work week (Abhik wrote about it here). Even managers can rely on getting consistent time (and support to make, if necessary) to focus and do creative work without the demand of constant meetings. We Built Ashby With The Quality, Breadth, And Depth That Many Customers Would Expect From Much Larger Teams Over Larger Time Scales. We’ve Done This Through Investment In • Great developer tooling. Our CI/CD takes ~10m, and we deploy at least 5x a day. Everyone on the team has contributed to developer experience., • Building blocks to create powerful and customizable products fast. At the core of Ashby is a set of common components (analytics modeling and query language, policy engine, workflow engine, design system) which we are constantly improving. Each improvement to a common component cascades throughout our app. Here’s an impromptu quote from Arjun in our company Slack of what it’s like to build a feature at Ashby: Give Engineers Ownership & Autonomy We, as engineers, find clever ways to solve problems, which amplifies when we deeply understand the problem. All of us in technical leadership did our best work as engineers when we had a deep understanding of the end‑user and the business and ownership over the solution. Our engineering culture reflects this experience: engineers own projects end‑to‑end, from speaking with users to writing product specs to UX design. These are skills that often don’t get to practice as engineers, and, as a manager at Ashby, you’ll provide mentorship and feedback to engineers to ensure they are successful when delivering projects. Diverse teams drive innovation and better outcomes. As the father of two young girls, I want to see them grow up in a world where all industries are open and welcoming to everyone, regardless of race, gender, or preferences. Helping to build a more diverse team at Ashby is my way of contributing to this change. Today, 26% of engineers at Ashby are from underrepresented groups. It’s not great, and we are taking conscious steps to improve, like sourcing diverse candidates, providing generous paid family leave, no leetcode interviews, and more. At Ashby, Our Team And Interview Process Want To Help You Show Your Best Self. We’ll Dive Into Past Projects And Simulate Working Together. Our Interview Process Is Six Interviews In The Following Order • Intro Call (30m) - Discuss your application questions, align on the responsibilities of the role, and answer questions about Ashby., • Past Experience Deep Dive (1h) - Discuss your past experience as an engineering leader., • Technical Screen (1h) - Add a feature back to Ashby. You’ll spend most of your time understanding a specific part of our codebase and write less than 15 lines of code., • Coffee Chat with VP of Engineering (1h) - Spend time with our VP of Engineering and get to know each other., • Meet the Team (2h) - At this point, the engineering leadership team is excited about you and you’ll meet our CEO, Engineers, Product Managers, and some other folks on the team. I will be your main point of contact and prepare you for interviews. If we don’t give an offer, we’ll provide feedback! I’m sharing our tech stack with the caveat that we don’t require previous experience: TypeScript (frontend & backend), Node.js, React, Apollo GraphQL, Postgres, Redis. • Competitive salary and equity., • 10-year exercise window for stock options. You shouldn’t feel pressure to purchase stock options if you leave Ashby —do it when you feel financially comfortable., • Unlimited PTO with four weeks recommended per year. Expect “Vacation?” in our one‑on‑one agenda until you start taking it., • Generous equipment, software, and office furniture budget. Get what you need to be happy and productive!, • $100/month education budget with more expensive items (like conferences) covered with manager approval. Ashby’s success hinges on hiring great people and creating an environment where we can be happy, feel challenged, and do our best work. We’re being deliberate about building that environment from the ground up. I hope that excites you enough to apply. Ashby provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. #J-18808-Ljbffr

• We are looking for a Senior Optimisation Developer with a strong mathematical background and experience in numerical modelling or mathematically intensive software development, • This is a hands-on senior software development technical role within the USC Optimisation team, • The team develops advanced optimisation technology that helps refineries improve operational efficiency and supports complex refinery planning, • The position is ideal for someone who can independently investigate complex problems, work effectively in an established codebase, and grow into broader technical leadership over time, • Contribute directly to the design, implementation, maintenance and improvement ofindustrialoptimisation software and related numerical modelling components, • Investigate complex mathematical, algorithmic and software engineering problems independently and drive them through to resolution, • Take ownership of large or technically challenging work items, breaking them down into manageable tasks and making sound implementation decisions with minimal supervision, • Work effectively withinanexisting and in someareaslegacy codebase, balancing respect for established team practices with thoughtful technical improvement, • Apply strong mathematical reasoning to modelling, optimisation and algorithmic challenges, • Supportthe robustness, performance,qualityand maintainability of optimisation code through effective debugging,profilingand diagnosis of build/runtime issuesthrough extensive automated unitand regressiontesting, • Demonstrate the potential to lead technical projects or workstreams over time, even where no formal leadership responsibility is assigned initially, • Provide guidance, coaching and technical support to less experienced developers whereappropriate, • Time off: 28 days of annual leave, plus bank holidays. You can also buy/sell five days a year, • Emergency leave: Five days a year to use when unexpected or urgent events make it impossible to work, • Hybrid working: The default option for employees is a 3:2 split between the office and working from home. Some positions are fully remote and others are fully office-based—refer to the job listing for specific details, • Parental leave: Maternity leave comprises 18 weeks at full pay, followed by 21 weeks statutory pay and 13 weeks unpaid. Paternity leave is two weeks at full pay. Pension contributions and benefits are maintained throughout, • Workplace nursery scheme: Pay for your child’s nursery directly through payroll, saving tax and NI contributions, • Electric care lease: Use your flexible benefits fund to subsidize the pre-tax leasing of a brand-new electric or ultra-low-emission car, • Shopping vouchers: Use your flexible benefits fund on discounts and vouchers for many major retail, tech and restaurant chains, • BUPA private healthcare: BUPA healthcare is a core benefit for employees. Use your flexible benefits fund and/or salary sacrifice to add family members, • Anonymous counselling: Through our Modern Health benefit, employees and their dependents over 13 are eligible to use our mental health app and receive unlimited counselling and coaching each year, • Dental insurance: Use your flexible benefits fund to cover preventative and restorative treatment. You can also add coverage for family members, • Cycle to work: Buy a brand-new bike and save 25–40% on retail price thanks to tax savings, • Gym membership: Use your flexible benefits fund to discount a membership to a major gym chain, • Bonus: Based on a combination of your own performance and AVEVA’s financial results, • Pension: Use your flexible benefits fund to increase the standard employer contribution. You can also route your bonus directly into your pension, saving tax and NI, • Income protection: Secure a reliable income if you’re unable to work due to long-term sickness or injury, • Life assurance: In the event of your death, your loved ones will receive a lump sum, • Charitable giving: The Action for Good program gives you three days of paid volunteering every year, as well as match funding opportunities. You can also use your flexible benefits fund to give to charity pre-tax, • Professional development: Access to LinkedIn Learning gives you the chance to grow your knowledge and skills, while AVEVA’s extensive mentorship network allows you learn from colleagues across the company, • Education support: After one year with AVEVA, you can apply for support towards a relevant course or qualification. AVEVA will reimburse up to 70% of the cost, • Service recognition: Whether you’ve been with us for 12 months or 50 years (it’s happened!), the AVEVAversary program rewards you during milestone years with cash and time off. We also recognize your contributions by planting a tree in the AVEVA Forest, our global forest of recognition The ideal candidate will have both postgraduate/research experience and industry experience however, candidates with either are encouraged to applyProgramming ability is required, but prior C++ experience is not essentialExperience in linear algebra and/or Lagrangian analysis is highly desirableTheoretical physicsApplied mathematicsComputer science with significant numerical or algorithmic depthEngineering disciplines with strong mathematical modelling contentRelevant industrial, research or advanced technical experience We welcome candidates from a range of mathematically intensive backgrounds with experience in modelling, simulation, or similar analytical fields. Relevant academic or professional backgrounds may include: Demonstrated potential to lead projects or technical workstreams, even if formal leadership experience has not yet beenrequiredAbility to communicate technical concepts clearly and work collaboratively with other developersProvenprogramming ability in at least one relevant language.(e.g. C++, C, C#, Fortran)Other computational scienceAbility to work effectively in a complex and evolving codebaseStrong mathematical background, supported by a postgraduate qualification (MSc, PhD, or equivalent experience)Experience of numerical modelling or mathematically intensive software developmentOperations researchExperienceusing andmaintainingbuild and meta-build systemsExperience of debugging tools, including debuggers, performanceprofilersand memory profilersExperience with source control systems and continuous integration/continuous developmenti.e.git and Azure DevOpsBackground in one or both of:Linear algebraLagrangiananalysisCritical thinking– evaluates evidence objectively and makes reasoned technical judgementsProblem solving– able to break down difficult technical and mathematical problems and develop practical, effective solutionsCoaching– supports and uplifts others through knowledge sharing and technical guidanceCollaborative relationships– works effectively with colleagues across the team and wider organisationInfluencing– able to shape technical direction through credibility,logicand constructive argument rather than authorityConceptual thinking– able to think beyond the immediate task and consider broader architectural, mathematical or maintainability implicationsTechnical leadership potential– shows the capacity to grow into a broader leadership role over time through ownership,judgementand consistency #J-18808-Ljbffr

We’re looking for a curious, rigorous, problem-hungry platform engineer (who codes!) to carry the ball as we bring Ashby to the big leagues. Ashby builds software that lets talent teams build an efficient, delightful, respectful hiring process. Similarly, you’re an engineer who wants to build a “paved road” that excellent engineering teams can safely take to the moon and back. We have notable customers like Notion, Linear, Shopify, and Snowflake. Our growth and retention metrics are best-in-class among our peers: we have tens of millions in ARR, growing >100% year over year, over 2500 customers, very low churn, and many years of runway. We’ll share more details once we meet, but you now probably have a good idea as to why we're hiring for this role. We’ve listed this role twice: as a Platform Engineer and Site Reliability Engineer – our team does both, and we are open to candidates who lean towards one or the other. Hi I’m Colin, Head of EMEA Engineering. I’ve spent a number of years leading engineering teams in startups, and that has always included being close to infrastructure teams - no matter what name they’ve worn (SRE, infrastructure, platform, etc). I’ve got my hands dirty building the initial infrastructure for startups and know the value a talented infrastructure engineer brings. The rigour, the discipline, the peace and quiet when everything just hums along. Our infrastructure is in a good place for now. Nothing is static. Ashby continues to grow rapidly, putting strain on our existing infrastructure. We’re always looking to give our customers more powerful hiring software, and building new product features often requires new pieces of infrastructure. Having herded plenty of snowflakeservers in the past, I’ve learned there’s a better way. I (and Ashby) place a lot of value on infrastructure-as-code. As a Platform Engineer at Ashby, you’ll get to dive into scaling problems, add new capabilities to our platform, and think about how our entire team interacts with infrastructure. All our own engineers own their projects end-to-end and ship with minimal oversight. We don’t put roadblocks to ensure security when common sense will do and we don’t build processes like change management boards around the lowest common denominator. But with great power comes great responsibility: we handle personal and confidential data about some of the biggest decisions we ever make at work. As we grow, more and bigger customers rely on us to be reliable and secure and how we operate internally will need to evolve. We’re at an inflection point where our ability to scale and deliver a seamless experience has a make-or-break impact – we have some of the fastest growing companies using our platform every day to hire hundreds of people per month. We need someone like you to make good decisions, debug thorny issues, and build us a future-proof platform that can withstand this scale. Our small but mighty infrastructure team has set up a secure and simple environment (we don’t believe in spinning up a new service unless necessary!) for our growing product team to build in. That’s where you come in: you, too, will own projects end-to-end and have an impact on core parts of the Ashby developer and user experience. For instance, you could work on: • Optimize our homegrown ultra-dynamic recruiting DSL-to-SQL compiler, and create tools to help developers do so, • Create automated guardrails for the security and privacy of our customer data, • Help our developers ship features fast through canary deploys, gradual rollouts and feature flags, while keeping complexity manageable and reducing downtime, • Work with the business and the engineering team to define SLOs and implement the corresponding SLIs., • Ensure all communication with external services supports retries and circuit-breakers., • Implement the infrastructure to support an event-driven architecture and data warehouse. We’re looking for someone who can build systems that an engineer would like to work with: mature and boring but open-minded and approachable. We have to balance reliability with flexibility. Software and its availability are now mission critical to almost every working professional. To be in an SRE in today’s world, you have to be extremely comfortable evaluating risk, those you take and those others take. • You never stop. You get weirdly obsessed about a problem that doesn’t yet make sense, turn it every which way in your head until the explanation dawns. You’ll search every rock, inventory every clue, hunt every mismatch. We do that, too - together we’ll be armed with state-of-the-art monitoring tools and an impressive amount of data, and join you in the adventure., • You don’t take shortcuts. You’re speaking up for the future user, the edge case, the doomsday design. You know product engineers want to build it with you, and see them as allies, where you give them the power and knowledge to access greater things., • You’re someone who cares about what you do and the team you do it with, and want to work with others who do as well. You’ll be on interview panels choosing your next colleagues, and you’ll take that seriously. You only want to work with people who make you better, and want to make you better., • You’ve built infrastructure at a slightly later stage than Ashby is at - you know how to deal with millions of data points, have seen great (or not great) infrastructure make or break customer experience, and have automated everything from provisioning to monitoring and release process., • You’re a Swiss army knife (all nationalities welcome ). You’ll get every hard problem the company faces. You’ll get to do infrastructure updates, security enforcements, database optimization, Kubernetes debugging, and digging through Typescript traces figuring out what doesn’t work. You probably don’t feel like an expert at at least some of that... and that appeals to you. All that makes for a pretty specific kind of role, and the job isn’t to everyone’s tastes! You should not apply if: • You don’t want to make your own decisions on what is the best paved road to build for Ashby, and expect a lead or manager to make the final call on what that is. Our leads (and managers) give ample commentary and feedback on technical decisions and how they’re made, but you ship what you want to build and are accountable for it., • You hate SQL. We have a lot of features built around making the best out of data, and our platform engineers also sometimes dive into a gnarly report or advise engineers on a more performant data model to use., • You don’t want to code. Our SREs are some of our best software engineers and they are just as responsible for the application as the other engineering teams - albeit at a platform level. Reviewing code and submitting code changes will be part of your day to day., • Your primary mode of communicating best practices to engineers is live meetings. We’re a very async culture and written communication (and code) is how changes get made. As an Ashby SRE, you will need to share new tooling and best practices with engineers faster than your next meeting opportunity will take you., • You’ve never delivered a project, on your own, without someone prodding you for updates. We have no project or delivery managers to fill your calendar with busy work, but the flip side is you have to do your project management, seek the help you need to get unstuck and cut scope when it’s worthwhile. I’m sharing our tech stack with the caveat that we don’t require previous experience in it: TypeScript (frontend & backend), Node.js, React, Apollo GraphQL, Postgres, Redis. We use Datadog and Sentry on 100% cloud-based (AWS) infra. We take developer experience and reliability seriously: all engineers are on call in a follow-the-sun model, and everyone contributes to developer tooling. As engineers, we are used to tooling that makes us better at what we do. When we started Ashby, we saw the opposite with Talent Acquisition software. Recruiting teams were leveling up how they did their work, but instead of software meeting this new standard, it held them back. Scheduling a final round is an excellent example. Recruiting teams wanted to schedule candidates faster, track interviewer preparation and quality, and do it with half the headcount. A recruiter needed to manually collect availability from the candidate, identify qualified interviewers, perform “Calendar Tetris” to find who is available to interview the candidate, schedule on the earliest date possible, and make any last‑minute adjustments as availability changed. They must do this while considering the interview load on each individual and whether interviewers need to be trained and shadowing others. TA software didn’t help. As hiring managers, we know TA is a critical function, and as engineers, we know software can do better. So, we built and continue to build Ashby to give TA teams the highest standard of tooling. Software that’s intelligent and powerful. Software that provides insights into where they’re failing and automates or simplifies many of the tasks they’re underwater with. We want other functions and departments to be jealous of what TA teams can do with Ashby, and today they often are! Our Engineering Culture Is Motivated By Abhik And Benji’s (our Co-founders) Belief That a Small Talented Team, Given The Right Environment, Can Build High-quality Software Fast (and Work Regular Hours!). We Do It Through • Minimal process with ownership over decisions normally made by product and design, • Natural collaboration and deliberate communication, • Investing in tools and abstractions that give us leverage, • Putting effort into building a diverse team The best engineers we’ve worked with delivered reliably magical outcomes. They took customer problems and relentlessly drove them to solutions that were not only successful but often brilliant and creative. While they did this with minimal oversight, stakeholders were never in the dark as to what was going on, and no setback was a surprise. Traditional product-development processes aren’t meant for the best engineers. Their purpose is to create consistent outcomes regardless of the engineer’s skill. But, consistency comes at the expense of an engineer’s time and freedom—both ingredients necessary to generate those magical outcomes. As a result, process stifles the best engineers and doesn’t give others the opportunity to practice the behaviors that made the best engineers the “best.” At Ashby, we want to build an environment that encourages every engineer to be their best. So, at Ashby, every Engineer runs their project. Product Managers (and Designers) build strategy, do customer research, and hand off problem briefs to Engineers. Engineers take on the rest: they research the problem, write product specs, build wireframes, and implement their solution end-to-end. We rely on engineers, not process, to push information outward to the relevant folks (e.g., Product Managers) and pull folks in to help (e.g., Designers, Infra). It’s a new level of ownership for many engineers, but we’d rather an engineer fail a bit and coach up their skills than use process as a crutch. Not everyone succeeds in our culture, but those who do thrive. Our engineering team consists of lifelong learners who are talented but also humble and kind (meet them here!). These attributes create an environment where collaboration happens naturally. We combine this with research, prototyping, and written proposals to see around corners and get feedback from the team across time zones. Focus time is something that we hold sacred, and, with thoughtful and deliberate communication, engineers are in 2h meetings per week (Abhik wrote about it here). To Drive It Home, Here’s a Recent Calendar Of An Engineer Who Has Been With Us For Over 4 Years. ~34 Hours Of Focus Time, 2.5h Of Interviews, And 3.5 Hours Of Meetings We also meet in person at least twice a year, once as a department and once as a company. You also have a small budget to meet up with folks in your city/region. We Built Ashby With The Quality, Breadth, And Depth That Many Customers Would Expect From Much Larger Teams Over Larger Time Scales. We’ve Done This Through Investment In • Great developer tooling. Our CI/CD takes ~10m, and we deploy at least 15x a day. A debugger that works out of the box. Everyone on the team has contributed to our developer experience., • Building blocks to create powerful and customizable products fast. At the core of Ashby is a set of common components (analytics modeling and query language, policy engine, workflow engine, design system) that we constantly improve. Each improvement to a common component cascades throughout our app (short video below)., • AI-powered tooling. We think of AI as a way to automate the mundane parts of building and maintaining high-quality software. We use a combination of third‑party and internally built tools that, for instance, auto-triage customer issues, suggest fixes, prototype ideas, generate production‑ready code, and conduct code reviews. Engineers have an unlimited token budget (but are not measured on it). We write in detail about our philosophy, current use of AI, and future plans for AI in Engineering here. Diverse teams drive innovation and better outcomes. Having seen my mother and partner build their careers as minority women in non‑diverse fields, I want to make sure Ashby creates opportunities for the next generation of engineers from underrepresented groups. Today, 25% of engineers and 50% of our engineering leaders at Ashby are from underrepresented groups. We are taking conscious steps to improve, like sourcing diverse candidates, providing generous paid family leave, no leetcode interviews, and more. At Ashby, our team and interview process want to help you show your best self. We’ll dive into past projects and simulate working together via pair programming, writing product and tech specs collaboratively, and talking through decisions. There are no leetcode or whiteboard exercises. • Introduction call with Hiring Manager (15 to 30m, live), • A technical screen where we pair in our actual codebase (1h, live), • Three non‑coding interviews that focus on technical design, debugging incidents, and infrastructure (3h 15m, live can be split across multiple days) Depending on our leadership team’s bandwidth, we may start with an additional 30m screen with a recruiter. Your hiring manager will be your main point of contact and prep you for interviews. Each round will have written guidance so you know what to expect (you’ll need minimal preparation). You’ll meet 4 to 6 people in engineering (with 5-15 minutes in each interview to ask them questions). If we don’t give an offer, we’ll provide feedback! We want an exceptional onboarding experience for every new hire. At Ashby, your dev environment is set up with a single script, you push your first product change on day one, and you spend the rest of your time shipping product changes that give you a tour of our codebase and best practices. The product changes increase in scope and ambiguity from simple copy changes to the delivery of a prominent, impactful feature. Your manager will do a 30, 60, and 90-day review to give feedback and calibrate on how we work together. It’s a team effort to get you successfully onboarded; you’ll have a peer paired with you to answer questions, pair program, and check in often to see if you need help. The rest of the team will run training sessions on our culture, product, engineering process, and technical architecture. • Competitive salary and equity., • 10-year exercise window for stock options. You shouldn’t feel pressure to purchase stock options if you leave Ashby — do it when you feel financially comfortable., • Unlimited PTO, and we will encourage you to take it., • A minimum of 12 weeks of fully paid parental leave, covered by Ashby. For folks outside the US, it may be longer to be in line with regional requirements., • Generous equipment, software, and office furniture budget. Get what you need to be happy and productive!, • $100/month education budget with more expensive items (like conferences) covered with manager approval., • If you’re in the US, we offer top‑tier health insurance for you and your dependents, with 100% of premiums covered by Ashby. In other countries, we provide high‑quality supplemental health insurance for you and your dependents, also fully covered by us. Ashby’s success hinges on hiring great people and creating an environment where we can be happy, feel challenged, and do our best work. We’re being deliberate about building that environment from the ground up. I hope that excites you enough to apply. Ashby provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. Ashby is committed to a fair and transparent hiring process. We confirm that this advertisement is for an active, existing vacancy within our organization. Please be advised that we may use artificial intelligence-driven tools to assist our recruitment team in screening, assessing, and selecting candidates for this position. Compensation Range: £151K - £246K #J-18808-Ljbffr

About CommonAI CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing. The Opportunity Help evaluate proposed AI hardware before it is available as a finished chip. You will turn RTL designs into working FPGA prototypes and emulation experiments, giving SIL and its technology partners a practical way to explore design behaviour and architectural choices. The initial focus is on RTL prototyping and emulation. You will help choose a useful first design and platform, adapt and integrate the RTL, and establish repeatable build, bring-up and experimental workflows. Working with our partners and colleagues in software and simulation, you will connect observations from the prototypes to wider system studies. Your work will help establish what the experiments tell us about a proposed design, how those findings relate to simulator models and where further evidence is needed. • Adapt and integrate RTL for FPGA prototyping or emulation, working with the design owners and documenting changes needed for the prototype., • Develop and maintain synthesis, implementation, timing-closure and reproducible build flows for the selected platform., • Bring up and debug designs, developing tests and instrumentation to check functional behaviour and support repeatable experiments., • Develop or integrate the control, stimulus and data-capture facilities needed for the agreed experiments, working with software colleagues on host interfaces and integration., • Relate observations from emulation to the model being evaluated, explaining how prototype frequency, interface overheads and other limitations affect interpretation., • Help assess platform, toolchain and hardware requirements, and document workflows that colleagues and partners can reuse., • An example early project would be to take a partner's RTL design through FPGA implementation and bring-up, then instrument it to investigate a selected architectural choice and compare observations with a simulator model., • Hands‑on experience taking RTL through an FPGA prototyping or emulation flow and debugging the resulting system., • Strong digital‑design skills in Verilog, SystemVerilog, VHDL or an equivalent HDL, together with practical timing and verification judgement., • Experience with a relevant FPGA or emulation toolchain and the scripting needed to make builds and experiments repeatable., • The ability to collaborate across hardware and software boundaries and explain the conclusions and limitations of a prototype experiment., • Practical experience using AI coding agents, with the judgement to validate generated HDL, scripts and software., • Experience with processor or accelerator designs, multi‑FPGA partitioning, host interfaces or performance characterisation would be useful., • Depth with a relevant platform is sufficient; the team will choose the initial platform and design around the first useful study., • Help build UK AI capability and improve how investment and compute serve the public good., • Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities., • Shape a growing team with startup pace and close academic links., • Use frontier models and coding agents with a substantial tooling budget. The opportunity to have a high impact in a growing organisation Competitive salary package, including pension and benefits Professional development opportunities Networking opportunities with influential figures from across the tech sector and academia A vibrant office environment located a few minutes' walk away from Cambridge train station Hybrid, with Cambridge attendance agreed individually around collaboration and the work; applicants across the UK are welcome. We are open to permanent employment, part‑time arrangements and consultancy. We would like you to start as soon as practical and can be flexible for the right person. We particularly welcome experienced engineers and can also consider earlier‑career candidates with strong evidence of ability. Relevant postgraduate study is useful, but qualifications are secondary to experience and the quality of your work. CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace. #J-18808-Ljbffr

Our client, a global tech company, offers data‑centric software solutions to major blue‑chip and government organisations. The role is a senior, hands‑on position within a cross‑discipline Agile product team. Location / WFH: Hybrid: 1–2 days a week in Cambridge office, remaining days remote. What you will do: Design and develop data‑centric software. You will use C# .Net backend with TypeScript / React frontend, and work with Snowflake, Azure, Python and SQL. You will own projects across the full development lifecycle, from architecture and design through to delivery. • Strong C# .Net backend skills, • Frontend experience with React and/or TypeScript, • Azure cloud experience, • Data‑centric mindset with experience in Snowflake and SQL; Python is a plus but not essential, • Collaborative, good communication and problem‑solving; able to mentor junior engineers, • Degree in a STEM discipline, • Salary up to £70k, • Bonus, • Private medical insurance plus well‑being benefits, • Pension and life assurance, • Inclusive, diverse environment; committees for wellness, charity and volunteering, DE&I, • Team and company socials Apply now to learn more about this opportunity. Client Server is an equal‑opportunity employer. We celebrate diversity and are committed to a workplace free of discrimination based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status. Mid‑Senior level Full‑time Information Technology and Engineering – Software Development #J-18808-Ljbffr

Remote Mission The mission of Speechify is to make sure that reading is never a barrier to learning. Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity. Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high-growth startups like Stripe, Vercel, Bolt, and many founders of their own companies. Overview We're looking for a Software Engineer - AI Data to join Speechify's AI team and build the data pipelines that power our model training and next-generation AI products. We build high-quality datasets at petabyte scale and low cost by combining engineering, infrastructure, and research. We're looking for a strong software engineer who enjoys solving complex problems, exploring new data sources, and building systems that make AI training more efficient and scalable. What You’ll Do: • Discover new sources of audio data and build reliable pipelines to bring them into our training datasets., • Build and improve large-scale data-processing systems, optimizing for data quality, throughput, and cost., • Collaborate closely with AI Scientists to improve training datasets and support the development of next-generation models., • Take ownership of engineering projects from problem discovery through implementation and continuous improvement. An Ideal Candidate Should Have: • A degree in Computer Science or a related field, or equivalent practical experience., • 5+ years of professional software engineering experience, with strong backend development fundamentals., • Proficiency in Python and Bash in Linux environments., • Experience building and operating production systems, ideally involving data pipelines or large-scale data processing., • Strong problem-solving skills, initiative, and the ability to work independently in ambiguous environments. Nice to Have • Experience with web crawlers, data acquisition, or distributed data-processing systems., • Experience with cloud infrastructure and Infrastructure as Code, particularly GCP and Terraform., • Familiarity with ML training data, dataset quality, or audio processing. What We Offer • A dynamic environment where your contributions shape the company and its products, • A team that values innovation, intuition, and drive, • Autonomy, fostering focus and creativity, • The opportunity to have a significant impact in a revolutionary industry, • Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture, • The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more, • An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain Think you’re a good fit for this job? Tell us more about yourself and why you're interested in the role when you apply. And don’t forget to include links to your portfolio and LinkedIn. Not looking but know someone who would make a great fit? Refer them! Speechify is committed to a diverse and inclusive workplace. Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Create a Job Alert Interested in building your career at Speechify? Get future opportunities sent straight to your email. Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf #J-18808-Ljbffr