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Senior Vice President, Model Risk Validation At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We are seeking a future team member for the role of SENIOR VICE PRESIDENT to join our MODEL RISK MANAGEMENT team. This role is located in NEW YORK. In this role, you will be focusing on validation and risk management of algorithmic trading models also with exposures to Market Risk and Pricing Modeling. • Independently perform end to end validation of algorithmic trading models, including analysis of model performance, assumptions, and limitations, design and execution of independent testing, documentation of validation findings, and communicating results to stakeholders., • Supervise model validations, model risk management activities through model lifecycle, and manage regulatory engagements, • Ensure effective processes and controls for prompt risk identification, assessment, mitigation, and tracking of issues related to model risk., • Behave ethically and adhere to BNY’s standards, including the Code of Conduct and applicable policies., • Demonstrate ownership and accountability for managing model risk holistically, engaging proactively with control functions., • Serve as a role model in creating and sustaining a strong risk culture and support the development of team members., • Master's Degree or PhD in a quantitative discipline, including engineering, mathematics, physics, statistics, econometrics., • The candidate must have a superb quantitative and analytical background with a solid theoretical foundation coupled with strong programming, documentation, and communications skills., • Minimum 5 years (5 - 7 preferred) of modeling or validation experience in financial services., • Must have most recent experience with algorithmic trading modeling, including knowledge of market microstructure, limit order book dynamics, execution quality measurement, experience validating algorithmic trading strategies and strong understanding of risk controls for algorithmic trading. Experience with derivatives pricing modelling is a plus. Here’s a few of our recent awards: • America’s Most Innovative Companies, Fortune, 2025, • World’s Most Admired Companies, Fortune 2025, • “Most Just Companies”, Just Capital and CNBC, 2025 Our Benefits and Rewards: BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter. BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans. BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $102,000 and $171,500 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual departmen BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $102,000 and $171,500 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.

Application Deadline: Address: 151 W 42nd Street Job Family Group: Audit, Risk & Compliance Performs validation of models and assesses model risk to confirm model appropriateness and capability for a designated portfolio. Provides effective challenge during model development and communicates decisions regarding model use to the business/management to ensure transparency and understanding of models and model risks. Assesses model’s capabilities, stress points and limitations; assesses the associated model risk and the controls in place to mitigate identified risks. Teams and Culture: • Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do., • Ensures alignment between values and behaviour that fosters diversity and inclusion., • Regularly connects work to BMO’s purpose, sets inspirational goals, defines clear expected outcomes, and ensures clear accountability for follow through., • Builds interdependent teams that collaborate across functional and operating groups to create the highest value for all stakeholders., • Improves team performance, recognizes and rewards performance, coaches employees, supports their development, and manages poor performance. Key Responsibilities: • Develops validation strategies and plans to ensure appropriate type and level of validation of models is carried out., • Independently validates / tests models and their associated assumptions, benchmarks, and supporting documentation against model validation process, standards, guidelines and principles, which includes:, • Lead model validation efforts across various volatility regimes, including stochastic volatility, stochastic-local volatility, and jump‑diffusion frameworks., • Develop, enhance, and maintain independent benchmark models for exotic derivatives (e.g., autocallables, barriers, quantos, range accrual, variance products, hybrids)., • Analyze complex payoff structures and produce accurate pricing, Greeks, and scenario analyses., • Review and validate model calibration routines to vol surfaces, correlation structures, and multi‑asset dynamics, and assess the data for model development as well as inputs to the model;, • Design and implement scalable testing libraries using C++, Python, or similar high‑performance languages., • Compares validation results with model developer results for replicability., • Measures the effectiveness of validation and monitoring framework; recommends changes as required., • Identifies deficiencies, conditions for model use, recommends changes, and escalates as required; quantifies model risks, documents outcomes and communicates with stakeholders. (detailed work), • Identifies where corrective actions are required and escalates per guidelines; monitors and ensures corrective action is taken., • Optimize numerical methods (e.g., PDE solvers, Monte Carlo engines, adjoint methods) to improve performance and stability., • Coordinates and monitors the review and sign-off of model validation reporting including model inventory and model inventory attestations., • Mentor junior quants and contribute to long‑term quantitative research initiatives., • Collaborate closely with trading desks to deliver strategic analytics, improve risk metrics, and support trade ideation., • Provides technical advice and guidance to assigned business/group on implementation of the model validation framework, and resolution of model risk issues., • Makes recommendations to senior leaders on strategy and new initiatives, based on an in-depth understanding of the business/group., • Advanced degree (PhD or Master’s) in quantitative fields such as mathematics, financial engineering, physics, or computer science., • 15+ years of hands‑on experience in equity derivatives model validation or front‑office quantitative research., • Deep knowledge of stochastic calculus, probability theory, and numerical analysis., • Strong programming skills in C++ and Python; experience with distributed computing a plus., • Verbal & written communication skills - In-depth / Expert., • Analytical and problem solving skills - In-depth / Expert., • Familiarity with regulatory frameworks (e.g., FRTB, model risk governance) in a derivatives context. Salary: $150,700.00 - $261,800.00 Pay Type: Salaried The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: ___ About Us At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world. As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset. To find out more visit us at ___ BMO is proud to be an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law. BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to ___ and let us know the nature of your request and your contact information. Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

Interactive Brokers Group, Inc. (Nasdaq: IBKR) is a global financial services company headquartered in Greenwich, CT, USA, with offices in over 15 countries. We have been at the forefront of financial innovation for over four decades, known for our cutting-edge technology and client commitment. IBKR affiliates provide global electronic brokerage services around the clock on stocks, options, futures, currencies, bonds, and funds to clients in over 200 countries and territories. We serve individual investors and institutions, including financial advisors, hedge funds and introducing brokers. Our advanced technology, competitive pricing, and global market help our clients to make the most of their investments. Barron's has recognized Interactive Brokers as the #1 online broker for six consecutive years. Join our dynamic, multi-national team and be a part of a company that simplifies and enhances financial opportunities using state-of-the-art technology. This is a hybrid role (3 days in office / 2 days remote). About Your Team: Shape the Future of Market Integrity at Interactive Brokers. Interactive Brokers (IBKR) seeks a Quantitative Software Engineer to join our elite transaction surveillance team. You will leverage your quantitative skills and experience in financial markets to develop sophisticated detection systems that identify market manipulation, fraud, and money laundering attempts before they impact market integrity. Your work will directly influence how one of the world's largest electronic brokers protects the financial ecosystem. What will be your responsibilities within IBKR: • Architect next-generation surveillance models to detect emerging manipulation patterns across global markets, • Partner with compliance leadership to ensure surveillance systems meet and exceed regulatory expectations, • Translate your experience into algorithms that identify suspicious trading and cashiering activity with high accuracy, • Conduct sophisticated data analysis on massive financial datasets (hundreds of millions of daily orders, millions of daily trades), • Evaluate model performance to optimize detection accuracy while minimizing false positives, • Document methodologies to withstand regulatory scrutiny and examination. Which skills are required: Attention Candidates: If your experience is exclusively in bank risk departments building, VAR models or similar frameworks, please note this role involves fundamentally different expertise in surveillance technology and compliance systems. • Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related quantitative field, • Strong programming proficiency in Python, • Professional experience: 5+ years (3+ for Master's, 1+ for PhD) hands-on experience in market surveillance, • Domain expertise in at least one of:, • Large-scale financial data analysis (orders, trades, market data), • Market manipulation detection methodologies (spoofing/layering, insider trading, money laundering, fraud, etc.), • Regulatory-driven feature engineering, • Communication excellence in explaining complex surveillance concepts to diverse stakeholders. Good to haves: • Regulatory background at the SEC, FINRA, or major securities exchanges, • Advanced degree in a quantitative discipline, • Mastery of Python data science tools (pandas, scikit-learn, xgboost, catboost), • Deep understanding of market microstructure and trading strategies, • Specialized knowledge in AML and market manipulation typologies To be successful in this position, you will have the following: • Self-motivated and able to handle tasks with minimal supervision., • Superb analytical and problem-solving skills., • Excellent collaboration and communication (Verbal and written) skills., • Outstanding organizational and time management skills., • Competitive salary, annual performance-based bonus and stock grant, • Retirement plan 401(k) with competitive company match, • Excellent health and wellness benefits, including medical, dental, and vision benefits, and a company-paid medical healthcare premium., • Wellness screenings and assessments, health coaches and counseling services through an Employee Assistance Program (EAP), • Paid time off and a generous parental leave policy, • Daily company lunch allowance is provided, and a fully stocked kitchen with healthy options for breakfast and snack, • Corporate events, including team outings, dinners, volunteer activities and company sports teams, • Education reimbursement and learning opportunities, • Modern offices with multi-monitor setups

As a Quant Investment Associate, you will be the analytical engine behind our Fixed Income platform. You will not only build the models but also interpret the data to provide strategic recommendations on portfolio construction, tactical asset allocation, and risk-adjusted optimization. This is a highly visible, front-office role where your work directly impacts the alpha generation of our Fixed Income mandates. Key Responsibilities Portfolio Construction & Optimization • Quantitative Modeling: Design and implement robust frameworks for multi-sector Fixed Income portfolio construction (including Sovereigns, Corporates, High Yield, and Securitized products)., • Optimization: Develop and refine optimization algorithms (e.g., Mean-Variance, Risk-Parity, or Factor-based) that account for transaction costs, liquidity constraints, and regulatory requirements (e.g., Basel IV/Solvency II)., • Alpha Generation: Utilize systematic signals and alternative data to identify relative value opportunities across global fixed-income markets., • Scenario Analysis: Conduct "Stress-Testing" and "What-If" simulations to quantify portfolio sensitivity to interest rate shocks, spread widening, or geopolitical events., • Custom Tooling: Build and maintain proprietary Python-based libraries for bond pricing, yield curve fitting, and attribution., • Visual Dashboards: Develop real-time dashboards (using Streamlit, Dash, or Tableau) to visualize portfolio exposures, risk concentrations, and performance drivers., • Ad-hoc Analytics: Rapidly respond to market events by performing deep-dive data analysis on specific sectors or idiosyncratic risks. Qualifications • Education: Masters or PhD in a STEM field (Financial Engineering, Mathematics, Physics, Statistics, or Computer Science)., • Experience: 3–10 years in a quantitative role within Fixed Income, ideally on the buy-side (Asset Management or Hedge Fund)., • Programming: Expert-level Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Experience with SQL and version control (Git) is essential., • Fixed Income Mastery: Deep understanding of duration/convexity, credit spreads, OAS, and the mechanics of structured products or derivatives (CDX, Swaps, Futures)., • Communication: Ability to bridge the gap between "Quant" and "PM"—explaining technical methodologies to non-technical stakeholders., • Commercial Acumen: A passion for markets and a drive to find profitable patterns in data., • Agility: Comfortable in a fast-paced trading floor environment where priorities can shift based on market volatility.

Empathy Talent is proud to be partnering with a leading national insurance and financial services organization currently investing heavily in enterprise AI and intelligent automation initiatives. Known for its long-standing reputation, customer-focused approach, and commitment to innovation, the company is continuing to expand its advanced analytics and AI capabilities to drive operational transformation across the business. The Opportunity Our client is seeking a Senior Data Scientist to help advance enterprise AI initiatives focused on intelligent automation, decision support, and next-generation AI applications. This role will focus heavily on Agentic AI, large language models (LLMs), generative AI, and NLP, with an emphasis on building scalable, production-grade solutions that improve internal workflows, customer experience, underwriting operations, and risk-related processes. You’ll work cross-functionally with data science, engineering, product, and business teams to design and deploy AI systems that deliver measurable business value in a highly regulated environment. Key Responsibilities • Design and deploy advanced Agentic AI and LLM-powered applications for enterprise use cases, • Build AI systems that automate workflows, improve operational efficiency, and enhance decision-making, • Lead projects through the full AI/ML lifecycle, including data preparation, model development, fine-tuning, validation, deployment, and monitoring, • Develop NLP pipelines, autonomous agents, and multi-step reasoning systems integrated into business platforms, • Apply generative AI and LLM technologies to interpret and process unstructured datasets such as customer interactions, operational documents, and domain-specific records, • Collaborate with data engineering, MLOps, AIOps, and product teams to build scalable and maintainable AI solutions, • Help establish AI development standards, governance practices, testing frameworks, and operational best practices, • Present technical findings and recommendations to both technical and non-technical stakeholders, • Stay current with emerging trends in Agentic AI, LLMs, reinforcement learning, and enterprise AI technologies, • Mentor junior team members and contribute to technical leadership initiatives What We're Looking For • PhD with 2+ years OR Master’s degree with 4+ years of experience in Computer Science, Engineering, Statistics, Applied Mathematics, or a related field, • 3+ years of hands-on experience building AI/ML solutions with a strong focus on Agentic AI, LLMs, and NLP, • Strong experience developing and deploying production-grade AI applications, • Expertise with generative AI, agent frameworks, retrieval-augmented generation (RAG), and multi-step reasoning architectures, • Strong Python programming skills, • Experience with frameworks and tooling such as Pytorch, TensorFlow, Hugging Face Transformers, LangChain and LangGraph, • Familiarity with classical machine learning methods including regression, clustering, XGBoost, Random Forests, and decision trees, • Experience with distributed computing, data processing, and scalable ML systems, • Understanding of software engineering best practices including Git/GitHub, testing, logging, and CI/CD, • Strong analytical, communication, and problem-solving skills, • Experience within insurance, financial services, underwriting, or regulated industries is highly preferred What’s on Offer Our client is committed to supporting the overall well-being of its employees through a comprehensive benefits program designed around mental wellness, physical health, financial security, and long-term career growth. This is an opportunity to join an organization that continues to invest heavily in both its people and innovation initiatives. • Competitive Compensation: Estimated base salary range of $119,000 – $195,000, depending on experience, location, and overall qualifications., • Performance Incentives: Opportunity for additional bonus or incentive compensation based on individual and company performance., • Flexible Hybrid Environment: Hybrid schedule with purposeful in-office collaboration and remote flexibility., • Comprehensive Healthcare Coverage: Medical, dental, vision, prescription, critical illness, accident, and supplemental insurance offerings., • Mental Wellness Support: Access to mental health resources, counseling support, caregiving assistance, grief support services, and wellness-focused programs., • Generous Time Off: Includes unlimited PTO for many roles, paid parental and family leave, volunteer time off, bereavement leave, and personal holidays., • Retirement & Financial Wellness: 401(k), HSA options, disability coverage, life insurance, financial wellness resources, and additional protection programs., • Professional Development: Tuition assistance and ongoing opportunities to work with advanced AI, Data Science, and Engineering teams on enterprise-scale initiatives., • Lifestyle & Family Support: Backup childcare and elder care resources, adoption assistance, fitness reimbursement programs, and employee discount offerings., • Inclusive Culture: Strong emphasis on collaboration, belonging, employee resource groups, and creating an environment where employees can bring their authentic selves to work. Additional Details • Hybrid schedule: 3 days onsite weekly, • Office locations include: New York, NY-- Boston, MA -- Holmdel, NJ -- Bethlehem, PA, • Candidates must be authorized to work in the United States without current or future sponsorship requirements

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit ___. We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments. In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations. This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team. You Will: * Develop and implement advanced behavior planning algorithms for autonomous vehicles * Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems * Design, write, and maintain efficient and scalable code in C++ and Python * Contribute to the architecture and continuous improvement of behavior planning software * Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms * Analyze system performance and implement enhancements based on data and feedback * Maintain comprehensive documentation of code, algorithms, and system designs * Work closely with other engineering teams to ensure seamless coordination and development You Have: * Proficient in modern C++ (11/14/17) and object-oriented programming * Skilled in Python for rapid prototyping and testing * Strong in debugging, profiling, and optimizing code * Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning * Familiarity with path planning algorithms like A*, RRT, or optimization-based methods * Master’s degree in Computer Science, Robotics, or a related field * Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field We Prefer: * Knowledge of state machines, behavior trees, and decision-making under uncertainty * Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT) * Knowledge of machine learning techniques, especially in the context of behavior prediction and planning * Experience with ROS / ROS2 * Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment * Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation * Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty * Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus

Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes. Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research. If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you. You will: • Build and deploy multi-agent systems for agentic reasoning validation, • Develop pipelines to detect errors and scale human judgment, • Combine classical ML, LLMs, and multi-agent techniques for reliability, • Lead research into agent failure modes and ship fixes, • Use AI tools to speed prototyping and iteration, • Build data-driven evaluations and deploy rapid improvements, • PhD or MSc in Computer Science, Mathematics, Statistics, or related field, • 3+ years shipping scaled production ML systems, • Demonstrated real-world impact, • Mastery of PyTorch, TensorFlow, JAX, or scikit-learn, • Deep expertise in agentic LLMs and multi-agent systems, • Strong software engineering and microservices (AWS/GCP), • Rapid, data-driven iteration, • Proficiency using AI tools to accelerate work, • Strong research depth with practical bias, • Experience prototyping agent evaluation/reliability systems, • Human-in-the-loop or annotation pipeline work, • Open-source contributions in agents, evaluation, or alignment About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

AssetWatch serves global manufacturers by powering manufacturing uptime through the delivery of an unparalleled condition monitoring experience, with a passion to care about the assets our customers care for every day. We are a devoted and capable team that includes world-renowned engineers and distinguished business leaders united by a common goal – To build the future of predictive maintenance. As we enter the next phase of rapid growth, we are seeking people to help lead the journey. We are hiring a Senior Applied AI Engineer to design and build reusable AI systems that accelerate innovation across the organization. This is a senior individual contributor role focused on rapidly prototyping LLM and agent-based workflows, architecting clean and reusable patterns, and partnering closely with our specialty data science team and Head of AI. You will translate strategy and ideas into structured, modular systems that can be handed off to production engineering teams or integrated via well-defined APIs. We expect end-to-end ownership, pragmatic tradeoffs, and a bias for action. Key Responsibilities AI Prototyping & Workflow Development • Design and build end-to-end LLM-powered workflows, including RAG pipelines, tool-calling systems, and agent architectures, • Rapidly prototype internal AI assistants and automation tools across business functions, • Integrate data science models into agent-based workflows, • Translate ambiguous ideas into practical, working systems Reusable Architecture & Enablement • Develop shared connectors to major LLM providers and internal data sources, • Create reusable agent templates and AI development patterns, • Design modular systems with clean API boundaries for production handoff, • Implement lightweight evaluation, logging, and tracing patterns appropriate for internal deployment Cross-Functional Collaboration • Partner deeply with specialty data science teams to operationalize models, • Work closely with the Head of AI to shape technical direction and AI strategy, • Communicate architectural decisions and tradeoffs clearly to technical and non-technical stakeholders Qualifications Education • BS in Computer Science, Engineering, Mathematics, or related field required; MS/PhD preferred but not required if experience demonstrates equivalent capability. Technical & professional experience • 6+ years of professional software or machine learning engineering experience building backend or distributed systems, • Strong proficiency in Python, including experience building modular, testable, and well-structured codebases., • Proficiency in SQL expected, including intermediate querying and basic ETL jobs, • Hands-on experience developing LLM-powered applications, including RAG pipelines, prompt orchestration, structured outputs, and tool-calling workflows, • Experience working with vector databases and designing retrieval strategies, • Experience designing and exposing RESTful or event-driven APIs for internal or external consumption, • Familiarity with agent frameworks or orchestration libraries (e.g., LangChain, LlamaIndex, Semantic Kernel, or similar), • Experience integrating ML or statistical model outputs into production-oriented systems, • Understanding of evaluation concepts for LLM systems (prompt versioning, offline evals, feedback loops, or guardrails), • Comfortable operating in ambiguity and driving initiatives end-to-end with minimal oversight Preferred • Worked in rapid prototyping and deployment ecosystems, • Experience building internal AI tooling, SDKs, or developer enablement frameworks, • Familiarity with cloud environments (AWS preferred), containerization (Docker), and basic deployment patterns, • Experience working with streaming or ETL pipelines for ingesting structured and unstructured data, • Exposure to observability practices (logging, tracing, metrics) in application systems, • Experience handing off prototypes to production engineering teams in a clean, scalable manner #LI-REMOTE What We Offer: AssetWatch is a remote-first company that puts people at the center of everything we do. We want our team members to thrive - that’s why we offer a range of benefits and perks designed to support your well-being, growth, and work-life balance. • Competitive compensation package including stock options, • Flexible work schedule, • Comprehensive benefits including retirement plan match, • Opportunity to make a real impact every day, • Work with a dynamic and growing team, • Unlimited PTO We have a distributed team that works remotely across locations in the United States and Ontario, Canada. Collaboration within core working hours is required.

At Dropbox, we believe in simplifying the way people work together. We provide a range of innovative cloud-based solutions to empower individuals and businesses to share, access, and collaborate on their files seamlessly. Engineering Managers are pivotal in shaping our mission of building a more enlightened way of working where everyone can unleash their creative potential without constraints. This role leads the Core Mobile Experience team, which owns most of Dropbox’s core user-facing mobile surfaces and is foundational to the File Sync and Share experience that underpins customer trust. As Engineering Manager, you’ll lead up to 25 engineers, drive high-impact outcomes through ambiguity, and foster a culture of innovation, ownership, and operational excellence. Working closely with cross-functional partners in a virtual-first environment, you’ll combine strong technical and people leadership to shape strategy and deliver meaningful business and customer impact. In this role, you will partner with a dedicated Product Manager to be the directly responsible individuals for executing on critical company-wide business objectives, with direct oversight from the CEO. They will accountable for the business impact of the same. Our Engineering Career Framework is ___ and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more ___. • Directly manage up to 25 direct reports, as a single execution unit, • Partner with multiple Product Managers to plan roadmaps and sprints, • Responsible for making tradeoffs between feature work and addressing long term technical debt, • Responsible for excellence in software quality, engineering practices and operations., • Lead their team through standard Agile processes, such as backlog management, stand ups, retros, etc, • Review and Approve engineering designs and able to set technical direction (in collaboration with a Technical Lead), • Drive cross-org initiatives while leading execution and actively supporting the career growth and development of your direct reports Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying. • BS, MS, or PhD in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent technical experience, • Minimum of 8 years of people management experience with an engineering team, • Minimum of 10 years as a software engineer or equivalent technical experience, • Must have experience managing engineering organizations of 20 or above, and experience managing managers, • Must have experience being a hands-on mobile engineer at a senior level, • Must have worked in a consumer user-facing team (versus a platform team, a developer-facing API-based product, etc), • Must have experience running a standard Agile process such as backlog management, stand ups, retros, etc, • Setting strategic direction on a consumer-facing product, • Experience building cross platform (iOS & Android) software US Zone 1 This role is not available in Zone 1 US Zone 2$223,400—$302,200 USDUS Zone 3$198,600—$268,600 USD

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Professionals — STEM Research Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities, and frontier problems where current models underperform., • Design challenging, rigorous domain tasks and write accurate, well-reasoned solutions that demonstrate expert-level scientific and technical reasoning., • Evaluate tasks and solutions produced by AI agents and other contributors, providing clear written technical feedback grounded in domain expertise., • Develop evaluation frameworks and rubrics for assessing scientific reasoning quality across STEM domains. Must-Have • PhD (completed, enrolled, or equivalent research track) in Physics, Chemistry, Biology, Mathematics, Statistics, Computer Science, Electrical Engineering, Mechanical Engineering, Civil Engineering, Materials Science, or another STEM discipline., • 3+ years of research, academic, or industry experience in their primary STEM domain., • Demonstrated technical expertise in at least one domain: computational modeling, laboratory methods, data analysis, statistical inference, programming, or equivalent scientific methods., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description Basic Qualifications: • Knowledge of different compilation steps (and ability to fix) in languages such as Go, C, C++, or Java., • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Ability to lead projects with several cross-org dependencies and design complexities, • Large-scale training using data structures and algorithms, • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning) Preferred Qualifications • PhD or equivalent in Computer Science, Engineering, Mathematics or related field, • 8+ years of experience in professional software development experience, developing and deploying systems in production environments, • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib, • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Anomaly Detection Techniques, • Deep Learning, • Scalable ML architecture, • Feature management, • Causal ML, • Reinforcement learning Anticipated base 250-280k + bonus + equity and comprehensive benefits

Global Financial Firm located in Jersey City, NJ has an immediate contract opportunity for an experienced Python Software Engineer Pay rate range: $ 81. Requirements: PhD or master’s degree in computer science, Data Science, Statistics, Mathematics, Engineering, or related field. Proficiency in Py

Global Financial Firm located in Jersey City, NJ has an immediate contract opportunity for an experienced Software Python Engineer Pay rate range: $ 87. Requirements: PhD or master’s degree in computer science, Data Science, Statistics, Mathematics, Engineering or related field.

Columbia Business School is seeking to hire a Staff Associate of research for the Decision, Risk, and Operations (DRO) Division. The work will include quantitative and qualitative research and analysis involving the collection, coordination, and management of information and data, development and implementation of computer models and simulations, development of research materials (figures, presentations, papers, etc.) and work on special projects relating to pertinent fields of research within the division. This position provides an opportunity to gain experience in academic business research, with a special focus on fields such as operations research, operations management, statistics, and economics; and it would be ideal preparation for a PhD program or other graduate study. The Staff Associate duties involve work in one or more of the following areas of research: Economics and Statistics. Specific duties include: • Collect, clean, and maintain datasets and databases. Extract and link data from multiple databases for analysis. Prepare detailed documentation., • Develop models and implement program code (STATA, Python, SQL, R, SAS, Matlab, etc.)., • Perform statistical analysis, including regression analysis and machine learning techniques., • Assist with data analysis and dissemination of findings through the preparation of reports, journal articles, presentations, websites, and other research outlets., • Perform case-based research, including work with detailed primary documents. Bachelor's degree in Economics or Finance or in a quantitative discipline such as Mathematics, Statistics, Engineering, Computer Science, Data Science, etc. • At least 6 months of experience in a research role or as a research assistant., • Programming experience in STATA is required. Strong preference for those who also know Python or R., • Additional programming experience in one or more of the following languages: SQL, SAS, Matlab, and/or C is preferred., • Familiarity with statistical tooks such as linear regression is required., • Demonstrated exceptional written and oral communications skills needed - a writing sample is required., • Expertise in processing large volumes of data and algorithm design expertise., • Experience in market design applications preferred., • Familiarity with text parsing and analysis (natural language processing) and/or machine learning techniques is preferred., • Candidate must be able to work on multiple projects simultaneously. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Engineer Type: Contract Compensation: $35–$75/hour Location: Remote Commitment: 10+ hours/week Role Responsibilities • Author original engineering questions that test deep conceptual understanding. Ensure questions are unambiguous, self-contained, and precisely defined., • Rate each question's difficulty: Medium (intro undergraduate), Hard (advanced undergraduate), or Expert (post-graduate and above)., • Provide 1 correct answer and 9 plausible but subtly incorrect alternatives that challenge expert-level solvers., • Write step-by-step Chain-of-Thought solutions with clear, concise intermediate steps in markdown format., • Supply 1–5 academic references per question from reputable sources such as peer-reviewed journals and university repositories. Must-Have • PhD or doctoral candidate in Engineering or a closely related field., • Master's degree considered for candidates with exceptional depth in a specific subdomain., • Strong command of graduate-level engineering principles, applied mathematics, and domain-specific standards., • Professional engineering licensure (PE) or industry experience is a strong plus., • Upload resume, • AI interview based on your resume

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Professionals — STEM Research Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities, and frontier problems where current models underperform., • Design challenging, rigorous domain tasks and write accurate, well-reasoned solutions that demonstrate expert-level scientific and technical reasoning., • Evaluate tasks and solutions produced by AI agents and other contributors, providing clear written technical feedback grounded in domain expertise., • Develop evaluation frameworks and rubrics for assessing scientific reasoning quality across STEM domains. Must-Have • PhD (completed, enrolled, or equivalent research track) in Physics, Chemistry, Biology, Mathematics, Statistics, Computer Science, Electrical Engineering, Mechanical Engineering, Civil Engineering, Materials Science, or another STEM discipline., • 3+ years of research, academic, or industry experience in their primary STEM domain., • Demonstrated technical expertise in at least one domain: computational modeling, laboratory methods, data analysis, statistical inference, programming, or equivalent scientific methods., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Generative AI Research Scientist, you'll work alongside our founders and team members to develop advanced generative models that can synthesize and design biological systems at multiple scales. Building upon our biological reasoning model, you'll focus on creating the generative capabilities that turn insights into innovations. * ⁠You will design and develop cutting-edge generative models specifically for biological data, creating AI systems that can generate novel molecular structures, protein designs, cellular components, and biological pathways. * You will design and implement state-of-the-art generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches and tailor them to biological constraints and properties * You will train and scale innovative AI models using large, diverse biological multi-modal datasets across distributed GPU clusters. * You will solve challenging AI research problems at scale, tackling key aspects such as model architecture and scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods. * Your work will span various advanced generative AI architectures, including transformers, diffusion models, and autoencoders, exploring and implementing these techniques to push the boundaries of biological AI. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You have extensive hands-on experience building and training generative models, such as diffusion models, GANs, VAEs, normalizing flows, or autoregressive models. * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects. * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description Only NJ residents apply. Summary/objective This position reports to the Chief Science Officer. We are seeking a passionate and experienced Analytical Chemist to join our team as a STEM Educator. This individual will play a key role in developing laboratory experiences that introduce students to advanced analytical chemistry techniques while fostering a love for science. You will instruct students in an analytical lab equipped with cutting-edge instrumentation, helping them gain exposure to professional methodologies and real-world applications. Why Join Us? • Be part of a mission-driven organization making a tangible impact on students' lives., • Work in a cutting-edge analytical lab with state-of-the-art equipment., • Collaborate with a dynamic team of educators and scientists dedicated to STEM education. (Full-Time Position, 40 Hours/Week, Monday–Friday, 8:00 AM – 4:00 PM) • Instruction and Mentorship:, • Design and deliver engaging, hands-on lessons for middle and high school students., • Explain complex analytical chemistry concepts in a way that is accessible and inspiring to students., • Provide mentorship and encouragement to students, nurturing their interest in STEM fields., • Train laboratory instructors and assistants on analytical instrumentation functions and use., • Train, advise and mentor participants of S2S’ pre-apprenticeship and apprenticeship program., • Lab Operations:, • Operate and maintain advanced analytical instruments, including HPLC, gas chromatography, mass spectrometry, UV/Vis spectroscopy, infrared spectroscopy, Inductively Coupled Plasma (ICP) spectroscopy, and other modern analytical laboratory tools., • Proficiency in wet chemistry techniques (assay development, sample and solution preparation, pH, dilution, and titrations)., • Guide students in performing experiments, analyzing results, and understanding data., • Ensure a safe and productive laboratory environment by following best practices in safety and instrument use., • Have a willingness to learn and instruct cross-discipline skills in STEM., • Curriculum Development:, • Develop and update curriculum content aligned with STEM educational standards and the goals of S2S., • Collaborate with the S2S team members to integrate analytical chemistry techniques and applications into current and future STEM experiences., • Community Engagement:, • Represent Students 2 Science in outreach efforts to schools, families, and partners., • Experience developing protocols, SOPs, or instructional guides., • Demonstrated experience with analytical techniques and method development (HPLC, gas chromatography, mass spectrometry, Inductively Coupled Plasma (ICP) spectroscopy, UV/Vis spectroscopy, and infrared spectroscopy). Candidates proficient at running, maintaining, and developing methods for GC and ICP are preferred., • Familiarity with maintaining and troubleshooting laboratory instrumentation., • Experience in teaching or mentoring middle and high school students preferred., • Ability to convey complex scientific concepts in an engaging and understandable manner., • A strong commitment to inspiring the next generation of scientists and promoting diversity in STEM fields., • Possess problem-solving and decision-making skills., • Highly organized with attention to detail., • Skill in using personal computers and a variety of software applications., • Excellent written and communication skills., • Detail oriented and work with a high degree of accuracy and efficiency., • Positive and happy demeanor - ability to work with others., • Must be self-directed and able to complete projects with limited supervision., • PhD in one or more STEM-related fields (Science, Technology, Engineering, and/or Mathematics), or equivalent related experience., • Health Insurance, • Flexible spending account, • Retirement plan, • Paid time off

Job Description We are sharing a specialised part-time consulting opportunity for PhD-level professionals experienced in advanced STEM research, technical problem design, scientific reasoning, domain-specific evaluation, and structured analytical task development. This role supports current and upcoming remote consulting opportunities focused on advanced scientific problem creation, domain-specific reasoning review, technical writing, research-informed task development, and high-quality project execution. Selected professionals will apply their subject matter expertise to create challenging problems in their field, evaluate technical reasoning, prepare structured written outputs, and support accurate, evidence-based STEM workflows. Key Responsibilities Professionals in this role may contribute to: Advanced STEM Problem Creation • Create difficult, domain-specific problems across fields such as mathematics, biology, chemistry, physics, computer science, statistics, economics, or related STEM areas, • Develop problems that require advanced reasoning, technical accuracy, and strong subject matter understanding, • Write clear reference solutions, expected reasoning paths, and structured answer explanations, • Review scientific or quantitative outputs for correctness, clarity, completeness, and reasoning quality, • Evaluate assumptions, calculations, methodologies, and conclusions against domain-specific standards, • Identify reasoning gaps, unsupported conclusions, ambiguity, and expected technical outcomes, • Apply PhD-level research experience to design challenging tasks grounded in real scientific, mathematical, computational, or analytical concepts, • Translate complex domain expertise into clear, structured, evaluable task formats, • Work independently on technical assignments requiring sustained focus and careful written communication Strong candidates may have: • PhD in a STEM field such as mathematics, biology, chemistry, physics, computer science, statistics, economics, engineering, or a related technical discipline, • Strong subject matter expertise and ability to design difficult problems within a specialized domain, • Excellent written and verbal communication skills in English, • High attention to detail and strong analytical judgment, • Ability to work independently and deliver high-quality technical outputs, • PhD from a U.S., U.K., Canadian, European, or comparable research university in a STEM field is strongly preferred, • Research experience, academic publications, teaching experience, technical writing, or advanced applied work is highly relevant, • Experience creating advanced problem sets, research tasks, technical assessments, or benchmark-style materials, • Background in teaching, tutoring, academic research, peer review, technical evaluation, or scientific writing, • Strong familiarity with mathematical notation, scientific methods, computational reasoning, data analysis, or domain-specific research tools, • Ability to explain complex concepts clearly and precisely, • Apply PhD-level STEM expertise to structured remote project work, • Contribute to high-quality scientific problem design, technical reasoning review, and advanced analytical task development, • Work on flexible assignments aligned with your academic or research background, • Use your subject matter judgment in a focused, rigorous review environment, • Independent contractor role, • Fully remote with flexible scheduling, • Expected commitment of approximately 15–20 hours per week, with potential for expanded availability depending on project needs, • Ongoing project structure with rolling applications, • Competitive rates between $65–$105 per hour depending on expertise, • Weekly payments via Stripe or Wise, • Selected professionals may complete a short interview as part of the process, • Projects may be extended, shortened, or adjusted depending on scope and performance This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: .

Job Description Location: New York / Hong Kong / Shanghai / Shenzhen / Beijing Function: Quantitative Research About the Role We are partnering with a rapidly growing, research-driven quantitative investment fund with a global footprint. The fund specializes in high- and mid-frequency trading strategies across equities and futures markets. Researchers play a central role in driving alpha discovery, end-to-end model development, and strategy optimization within a lean and highly collaborative environment. This is an opportunity for someone who wants full ownership of the research lifecycle, access to diverse datasets, and the chance to make a direct impact on trading strategies in a platform that values intellectual rigor and innovation. Responsibilities * Conduct quantitative research to identify alpha signals across equity and futures markets. * Build, test, and optimize statistical and machine learning models for trading strategies. * Analyze large, diverse datasets and extract actionable insights for mid- to high-frequency domains. * Collaborate closely with a research-focused team to drive the implementation of new models and strategies. * Stay at the forefront of academic research and translate it into practical trading applications. Requirements * Bachelors, Masters, or PhD in Statistics, Mathematics, Physics, Computer Science, or related quantitative field. * Proficiency in 1 programming language: Python (preferred), C++, MATLAB, R, or C#. * Strong analytical skills, intellectual curiosity, and structured problem-solving capability. * Ability to synthesize academic research and apply it to practical quantitative problems. Preferred Qualifications * Competition awards (e.g., IMO, IPhO, ACM-ICPC) or top-tier academic achievements. * Publications in peer-reviewed journals or conferences in relevant fields. * Prior experience in quantitative research, trading, or data-intensive environments is a plus. Why This Role? * Research Ownership: Lead projects end-to-end, from alpha discovery to strategy deployment. * Global Exposure: Work with a team across US and Asia offices. * Innovation-First: Access to diverse datasets and a culture of continuous R&D. * Career Growth: Lean teams allow high-impact contributions early in your career.

Job DescriptionWho we are The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it. Who you are Metropolis is seeking a Machine Learning Engineer to develop and expand our revenue forecasting and dynamic pricing systems. This position is part of the machine learning team within the Advanced Technology Group (ATG) and directly influences key business metrics, including revenue, utilization, and customer demand. In this role, you will design and implement models that predict demand, analyze price–demand relationships, and develop pricing strategies. This is a highly impactful role with significant ownership over data, modeling, and infrastructure systems. What you'll do • Design, develop, and productionize demand forecasting models optimized for different business goals (e.g., visits, revenue, availability), • Innovate and improve Machine Learning models for price elasticity, time series, and probabilistic models for revenue optimization, • Design and build end-to-end data pipelines to support large-scale production usage, • Identify data issues (e.g., bias, leakage, labeling inconsistencies) and drive solutions, • Design and analyze experiments (A/B, switchback, causal inference) to validate pricing strategies, • Deploy and monitor models in production, ensuring reliability, scalability, and data quality, • Collaborate with product, engineering, and business teams to translate requirements into scalable ML solutionsWhat we're looking for, • PhD in Computer Science, Statistics, Economics, Applied Mathematics, or a related STEM field, with at least 1+ years of relevant experience, or MS with equivalent publications, • Proficient programming skills in Python and SQL, • Foundational experience in machine learning modeling and statistics, such as time series forecasting, probabilistic models, and deep learning models, • Strong knowledge with forecasting, optimization, and decision-making algorithms, including revenue maximization, constrained optimization, and demand/price curve optimization, • Solid understanding of causal inference and experimentation, with experience evaluating both short-term and long-term effects (A/B testing, DiD, uplift modeling), • Hands-on experience with data pipeline development, including AWS data storage, data transformation, distributed processing (Spark), and workflow orchestration (Airflow), • Strong communication skills, both written and verbal, with the ability to operate effectively at team and deep technical levels When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $150,000.00 USD to $180,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-NM1 #LI-Onsite Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate's application relative to the required job qualifications and responsibilities listed in the job posting. As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records. Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

Job Description Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields. Responsibilities: • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed., • Implement, train, and validate proposed algorithms for specific problem domains., • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities., • Collaborate with others in a multidisciplinary team environment to accomplish research goals., • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory., • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings., • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques., • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods)., • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++., • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe., • Proven ability to undertake original research and communicate findings in peer-reviewed publications., • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions. We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world. If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.

Job DescriptionRole: Senior Quantitative AnalystRole DescriptionThe Market Data Solution (MDS) and Risk Master (RM) businesses are seeking a high caliber candidate to join as a Senior Quantitative analyst their Mumbai office. This is a high-profile role which requires strong modelling skills coupled with a strong commercial awareness and excellent communication skills. Knowledge of market data processes or data modelling would be very useful but is not essential.Reporting to the Business Owner for MDS and RM, the key responsibilities are as follows • Develop APIs to for both open source and bank in-house quantitative libraries and market risk engines for both calibration as well as valuation use cases, e.g., • Zero Curve Calibration / Bootstrapping, • Hull White Model Calibration, • Put-Call Parity Analysis on Market Vol Data, • SABR Model Calibration, • Cubic Spline Interpolated Zero Rates, • Credit Curve (Survival Probabilities) Calibration / Bootstrapping, • Risk Factor de-composition: Regression of NonModellable Z-Spread Risk Factor on comparable Modellable Z-Spread Risk Factors to determine Modellable Explained and NonModellable Unexplained Risk Factors, • PCA for Curve Validation, • FX Stochastic Volatility Model: Heston implementationThe role involves the integration of these APIs into the GoldenSource data model. To do this effectively the successful candidate will need to understand these models in the quant or market risk libraries, • Work with the development and pre-sales teams to prototype solutions for Market Risk and FRTB Use cases, e.g., • FRTB Risk Factor Eligibility Test, • Shock generation for Equity Vol Smile using gap filling, • Reconstruction of Equity Index time-series using proxy weightings, • Aggregation of risk sensitivities in Risk Warehouse for the standardized approachTo be considered for this role you will need to have the following:, • MSc or PhD in Financial Mathematics, Mathematics or Physics or equivalent work experience, • Strong Knowledge of option pricing theory and financial mathematic, • Experience in a quantitative role for interest rates, FX or equities gained in an investment bank, • Experience in model’s development, programming and maintenance of model’s libraries, • Knowledge of derivatives products, • Strong programming skills in Python, • Good data modelling skills including some experience with RDMS, • Strong Excel, • Knowledge of Hadoop or Java would be good but not essential, • Prior experience of Open Gamma Strata or QuantLib would be good but not essentialYou will also need strong communication skills and the ability to articulate complex problems and solutions to all audiences. In addition, you should enjoy working in a fast-paced environment and be able to work to tight timescales. Excellent analytical skills with a strong focus on accuracy of information coupled with determination are also desirable skills.

Job DescriptionData Science & Analysis - AI TrainingAbout Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for Data Scientists and Data Analysts to join our Expert Network to help train and evaluate cutting-edge AI models using real technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring • Education: a BS, MS, or PhD in Data Science, Statistics, Mathematics, or a closely related quantitative field., • Professional Experience: real-world experience in data analysis, predictive modeling, or machine learning engineering., • Technical Rigor: the ability to solve complex statistical problems and interpret high-level data visualizations independently., • Analytical Mindset: strong attention to detail with the ability to identify subtle logical fallacies in statistical reasoning or data interpretations., • LLM Fluency: significant experience using LLMs to assist with data workflows, with a clear understanding of where these models typically hallucinate or fail., • Communication: the ability to explain complex mathematical concepts or data insights clearly and concisely., • A PayPal account to receive payment from our clients What you'll be doing in the role • Evaluate LLM Responses: review AI-generated data insights and statistical analysis for accuracy, clarity, and completeness., • Fact-Check Technical Claims: use authoritative references to validate mathematical proofs, statistical formulas, and data-driven conclusions., • Validate Code & Outputs: execute data-related scripts (e.g., Python/R) to ensure they produce correct results and handle edge cases properly., • Annotate Model Performance: identify strengths and weaknesses in how a model reasons through data problems or builds predictive models., • Ensure Alignment: verify that model responses follow specific system guidelines and maintain a high standard of professional technical behavior. Key Technologies • Programming: proficiency in Python (Pandas, NumPy, Scikit-learn) or R., • Data Querying: advanced SQL for complex data extraction and manipulation., • Visualization: experience with tools like Tableau, PowerBI, or Matplotlib/Seaborn. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. The role: We're looking for a Senior Manager, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics—you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale. As Senior Manager, you'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution. Responsibilities:Strategic Vision & Product Partnership • Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes, • Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities, • Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems, • Translate complex product challenges into clear data science problems with measurable success criteria, • Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration, • Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.Team Leadership & Development, • Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems, • Foster a culture of innovation, experimentation, and continuous learning within the data science organization, • Create career development pathways that attract and retain top data science talent, • Collaborate with Analytics Engineering to ensure seamless model deployment and monitoringAdvanced Analytics & ML Capabilities, • Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey, • Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning, • Develop causal inference methodologies to understand true incrementality of product changes., • Ensure models are observable, explainable where needed, and continuously improved post-launchProduct Measurement & Impact, • Define product success metrics and measurement frameworks that align with business objectives, • Build scalable dashboards and monitoring systems that provide real-time visibility into product performance, • Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimizationQualifications:, • 8+ years of experience in data science, with at least 3 years in leadership roles managing data scientists or ML engineers, • Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling, • Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor, • Strong product sense and business acumen—ability to identify high-impact opportunities and translate them into data science initiatives, • Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical, • Excellent communication skills—ability to explain complex technical concepts to non-technical stakeholders and influence product strategy, • Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow), • Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)Preferred requirements:, • PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field, • Experience with real-time ML systems and feature stores, • Background in recommendation systems or two-tower/multi-modal embeddings, • Familiarity with generative AI and LLM applications in product contexts, • Experience building data science teams from scratch or through periods of rapid growth, • Prior work in subscription businesses or retention-focused products, • Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)What Success Looks Like, • 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan 📈 We grow, you grow: Stock Options Plan granted on Day 1 🌟 Eligible for a bi-annual performance bonus ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$225,000—$240,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description We are sharing a specialised part-time consulting opportunity for professionals experienced in engineering, academic assessment design, technical question authoring, applied mathematics, solution verification, and structured engineering content review. This role supports current and upcoming remote consulting opportunities focused on high-quality engineering assessment development, multiple-choice question writing, academic content verification, reference solution review, and rigorous technical reasoning evaluation. Selected professionals will apply their engineering expertise to author, review, and validate challenging assessment materials across core engineering domains. Key Responsibilities Professionals in this role may contribute to: Engineering Question Authoring • Create original, challenging multiple-choice questions across core engineering domains, • Design questions that test deep conceptual understanding, applied reasoning, technical judgment, and engineering problem-solving, • Ensure each question is precise, self-contained, unambiguous, and answerable based on the information provided, • Write clear reference solutions in structured markdown format, • Rate question difficulty across levels such as introductory undergraduate, advanced undergraduate, or postgraduate-level expertise, • Provide academic references from reputable sources such as peer-reviewed journals, university materials, or recognized technical resources, • Review pre-written engineering questions for accuracy, clarity, rigor, completeness, and solvability, • Flag issues involving ambiguity, missing assumptions, weak distractors, unclear wording, or incorrect answer logic, • Edit questions where needed and document the rationale for changes Strong candidates may have: • Advanced expertise in mechanical engineering, thermal engineering, electrical engineering, aerospace engineering, materials science, industrial engineering, systems engineering, civil engineering, or related engineering fields, • Strong command of graduate-level engineering principles, applied mathematics, modeling, and domain-specific technical standards, • Experience authoring, reviewing, teaching, grading, or verifying academic assessment content, • Ability to express complex engineering ideas clearly and concisely in written English, • Strong attention to detail and ability to identify subtle technical or conceptual issues, • PhD or doctoral candidacy in engineering or a closely related technical field is highly relevant, • Master's degree may be suitable for candidates with exceptional depth in a specific engineering subdomain, • Professional engineering licensure, industry engineering experience, research publications, university teaching experience, or academic assessment background, • Familiarity with mechanical and thermal systems, electrical systems, aerospace systems, materials science, civil infrastructure, industrial systems, or applied engineering design, • Experience preparing or reviewing exam questions, benchmark tasks, academic rubrics, reference solutions, or engineering problem sets, • Strong comfort with markdown formatting, technical notation, academic references, engineering terminology, and structured review workflows, • Apply advanced engineering expertise to structured remote project work, • Contribute to high-quality academic benchmark development, question authoring, solution review, and technical reasoning evaluation, • Work on flexible assignments aligned with your academic, research, or engineering background, • Use your technical judgment in a rigorous, detail-oriented review environment, • Independent contractor role, • Fully remote with flexible scheduling, • Part-time commitment of approximately 10+ hours per week depending on project availability, • Competitive rates between $50–$95 per hour depending on expertise, • Weekly payments via Stripe or Wise, • Projects may be extended, shortened, or adjusted depending on scope and performance This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: .

Job Description Job Title: Senior Data Scientist Location: United States (Can be based anywhere) Travel: As needed About the Role We are looking for a Senior Data Scientist to join a high-performing analytics team working on complex, real-world problems across multiple industries. In this role, you will collaborate with cross-functional teams to design, build, and deploy advanced analytics and AI solutions that drive meaningful business impact. You'll work on a variety of projects, ranging from optimizing operations to building machine learning and AI-driven applications, while continuing to grow your technical and problem-solving skills. Key Responsibilities • Translate business problems into data-driven solutions, • Perform exploratory data analysis and identify key insights, • Build, test, and deploy machine learning and AI models, • Develop and evaluate models using statistical techniques and experimentation (including A/B testing), • Work with modern AI approaches such as large language models (LLMs) and retrieval-augmented generation (RAG) when applicable, • Deploy solutions via APIs or data pipelines and monitor performance over time, • Collaborate with engineers and product teams to integrate solutions into applications, • Ensure models are accurate, explainable, and scalable, • Python and SQL for data science and analytics, • Distributed computing tools like Spark/PySpark, • Cloud platforms such as AWS, Azure, or GCP, • Tools like Airflow, Databricks, Docker, and Kubernetes, • Bachelor's degree with 8+ years of experience, or Master's/PhD in Computer Science, Statistics, Mathematics, or a related field, • Experience applying machine learning to real-world datasets, • Strong programming skills in Python and SQL, • Experience with large-scale data processing (e.g., Spark), • Familiarity with cloud environments and modern data tools, • Strong problem-solving and analytical thinking skills, • Excellent communication skills with the ability to explain technical concepts clearly, • Exposure to a wide range of industries and use cases, • Opportunities to work on cutting-edge AI and data science projects, • A collaborative, fast-paced, and learning-focused environment, • Strong mentorship and career growth opportunities

Job Description Position Description: A client of AlphaStaffHCM is looking for a Software Engineer with deep expertise in Mathematical Optimization and algorithm development. This role is critical in architecting the core software engine that drives our proprietary photonic quantum processors, combining complex mathematical formulations with physical optical hardware feedback. Responsibilities • Design and implement the high-performance C++ runtime and Hardware Abstraction Layer (HAL) for photonic optimization computers., • Profile and optimize critical execution paths to minimize latency, addressing bottlenecks in memory bandwidth, cache locality, and data transfer., • Collaborate with FPGA, Electrical engineers and Firmware engineers to ensure to create, test, and optimize device interfaces., • Develop algorithmic enhancements to usage of quantum feedback to solve NP hard optimization problems more efficiently with higher solution quality., • Write efficient, thread-safe code for concurrent hardware control and real-time signal processing., • Design and implement novel algorithms that map optimization and machine-learning problems onto entropy-based photonic quantum processors, including post-processing pipelines., • Build software layers to decompose and orchestrate large-scale optimization problems across multiple photonic hardware resources. Required Qualifications • 6+ years of experience in software engineering with a focus on systems or HPC., • Strong proficiency in C++ and Python, • Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer Linear Programming (MILP), or Gradient-Free Methods., • Experience with Numerical Analysis and high-performance math libraries (e.g., BLAS, LAPACK, Eigen)., • Familiarity with protocols (e.g., UART, SPI, gRPC, REST) and software integration., • Strong understanding of performance tuning, memory management, and fault-tolerant design., • Familiarity with Linux system programming and build toolchains (CMake, GCC/Clang)., • Experience working in cross-functional teams involving hardware, physics, and software. Preferred Qualifications • Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics., • Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks., • Familiarity with Open Quantum Systems or optical feedback mechanisms., • Background in Digital Signal Processing (DSP) or control theory., • Knowledge of containerized deployment using Docker. Skills C++, High Performance Computing (HPC), Algorithm Design, Mathematical Optimization,, Multi-threading, Linux, CMake, Python, Performance Profiling, Hardware Abstraction, Signal Processing. Disclaimers: AlphaStaff, Inc. and the Client are equal employment opportunity employers and do not discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, past or present military service, disability, genetic information, or any other basis protected by applicable federal, state, or local laws.

Job Description StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we're here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. The Role We're seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints. You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions. You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience. Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA What You'll Do • Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions., • Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale., • Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process., • Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift., • 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred., • Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost)., • Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement., • Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL., • Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact., • Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety., • Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring., • Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale., • Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact., • Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Machine Learning Research Scientist, Interpretability, you'll work alongside our founders and team members to develop AI systems capable of processing and reasoning across multiple biological data modalities simultaneously. * You will develop specialized methods for understanding our biological reasoning models, reverse-engineering how they represent and process complex biological information. * You will design and conduct experiments to uncover interpretable features across biological scales. * You will address unique challenges in biological model interpretation, such as disentangling the multi-scale, hierarchical representations of biological systems * You will build biology-specific visualization tools that can map model activations to meaningful biological concepts. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics, or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects/ * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description We are sharing a specialised part-time consulting opportunity for students, graduates, and professionals experienced in physics, chemistry, mathematics, biology, quantitative reasoning, scientific analysis, and structured problem-solving workflows. This role supports current and upcoming remote consulting opportunities focused on structured STEM problem solving, scientific reasoning review, analytical task execution, quantitative modeling, interdisciplinary analysis, and high-quality project delivery. Selected professionals will apply their STEM expertise to review scientific or mathematical problems, develop clear solutions, evaluate reasoning quality, and support accurate, evidence-based technical work. Key Responsibilities Professionals in this role may contribute to: STEM Problem Solving & Analytical Review • Work on structured problems across physics, chemistry, mathematics, biology, or interdisciplinary STEM topics, • Analyze scientific and quantitative problems using clear reasoning, appropriate methods, and source-supported conclusions, • Review problem statements, solution paths, calculations, assumptions, and expected outputs, • Apply quantitative methods, modeling, data analysis, or technical reasoning depending on task requirements, • Support review of analytical workflows involving formulas, datasets, experimental concepts, scientific models, or mathematical structures, • Prepare clear written explanations for technical conclusions based on provided materials and verifiable reasoning, • Produce concise, well-organized solutions for scientific, mathematical, or analytical tasks, • Communicate reasoning clearly in written form with step-by-step structure where appropriate, • Support interdisciplinary problem-solving workflows requiring independent thinking and careful execution Strong candidates may have: • Strong foundation in one or more STEM domains such as physics, chemistry, mathematics, biology, engineering, statistics, or related scientific fields, • Ability to analyze problems, apply structured reasoning, and produce high-quality outputs independently, • Familiarity with quantitative methods, modeling, experimental reasoning, or data analysis where relevant, • Comfort working on open-ended, technical, or interdisciplinary problems, • Clear written communication skills and ability to explain scientific or mathematical reasoning, • Bachelor's, master's, or PhD-level study in a STEM field is helpful, • Current students pursuing degrees in physics, chemistry, mathematics, biology, engineering, data science, statistics, or related fields may also be strong candidates, • Research, teaching, tutoring, laboratory, internship, or industry experience in a STEM field, • Experience with mathematical modeling, scientific writing, data analysis, coding, technical documentation, or quantitative research, • Familiarity with tools such as Python, R, MATLAB, Excel, Jupyter, statistical software, lab analysis tools, or domain-specific scientific software, • Experience explaining complex scientific ideas clearly and concisely, • Apply STEM expertise to structured remote project work, • Contribute to high-quality scientific reasoning, analytical review, and technical problem-solving workflows, • Work on flexible assignments aligned with your academic or professional background, • Use your scientific judgment in a focused, detail-oriented review environment, • Independent contractor role, • Fully remote with flexible scheduling, • Part-time commitment depending on project availability, • Competitive rates between $80–$90 per hour depending on expertise, • Weekly payments via Stripe or Wise, • Projects may be extended, shortened, or adjusted depending on scope and performance This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: .

Job Description Immediate Start - Machine Learning Researcher (PhD) – Systematic Commodities Hedge Fund Moreton Capital Partners is rapidly expanding and seeking a talented Machine Learning Researcher to help design and improve the predictive models that power our systematic commodities trading strategies in our Mexico City Office. We trade global commodity futures using machine learning, alternative data, and institutional-grade portfolio construction. Our edge comes from research depth, disciplined experimentation, and robust production systems. This role is for candidates completing or having recently completed a PhD with a strong machine learning, statistics, or applied mathematics focus who want to apply advanced research in a real capital environment. You will work directly with the CIO and sit alongside a world class international quant research team to turn cutting-edge ML ideas into live trading signals. Your research will ship to production and directly impact portfolio returns. This is not a purely academic role. We're looking for someone ready to hit the ground running and available to start immediately. In return, we offer a competitive salary, substantial performance share, comprehensive benefits, incredible work environment and a relocation package to make the move seamless. What you will work on • Designing predictive models for cross-sectional and time-series commodity returns, • Developing new features from price, positioning, options, macro, and alternative datasets, • Improving signal robustness and reducing overfitting through rigorous validation, • Combining and blending multiple models into portfolio-level forecasts, • Regime detection, meta-models, and adaptive allocation frameworks, • Model diagnostics, explainability, and stability analysis, • Translating research ideas into production-ready implementations, • Formulate research hypotheses and test them using clean, time-aware ML pipelines, • Build and evaluate models (tree-based, linear, ensemble, deep learning, etc.), • Run walk-forward and out-of-sample experiments with realistic costs, • Analyze information coefficients, turnover, drawdowns, and risk-adjusted returns, • Design feature engineering frameworks and reusable research tooling, • Document findings clearly and communicate results to portfolio managers, • PhD (completed or near completion) in Machine Learning, Statistics, Applied Mathematics, Computer Science, Physics, Engineering, or related quantitative field, • Strong Python skills and experience with scientific computing stacks, • Deep understanding of statistical learning and model validation, • Experience working with large datasets and experimental pipelines, • Ability to move from theory to practical implementation, • Intellectual curiosity and strong problem-solving mindset, • Experience with financial markets or systematic trading, • Familiarity with time-series modelling or forecasting, • Experience with LightGBM/XGBoost, deep learning, or ensemble methods, • Exposure to portfolio construction or risk modelling, • Experience with cloud or distributed compute environments, • Direct impact: your research drives live trading capital, • Research freedom: explore ideas with fast feedback loops, • Real-world data: large, messy, multi-source datasets, • Small team: high ownership and rapid iteration, • Strong learning curve across ML, markets, and portfolio construction, • Market leading benefits, • High responsibility from day one, • Attractive compensation: Highly competitive base salary and annual bonus that scales as the business grows., • Relocation package to our Mexico City office, along with a competitive benefits offering that includes health and life insurance, a year-end bonus, and generous paid time off., • Positive, inclusive and encouraging work environment., • Close collaboration across a global team.

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Professionals — STEM Research Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities, and frontier problems where current models underperform., • Design challenging, rigorous domain tasks and write accurate, well-reasoned solutions that demonstrate expert-level scientific and technical reasoning., • Evaluate tasks and solutions produced by AI agents and other contributors, providing clear written technical feedback grounded in domain expertise., • Develop evaluation frameworks and rubrics for assessing scientific reasoning quality across STEM domains. Must-Have • PhD (completed, enrolled, or equivalent research track) in Physics, Chemistry, Biology, Mathematics, Statistics, Computer Science, Electrical Engineering, Mechanical Engineering, Civil Engineering, Materials Science, or another STEM discipline., • 3+ years of research, academic, or industry experience in their primary STEM domain., • Demonstrated technical expertise in at least one domain: computational modeling, laboratory methods, data analysis, statistical inference, programming, or equivalent scientific methods., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Engineer Type: Contract Compensation: $35–$75/hour Location: Remote Commitment: 10+ hours/week Role Responsibilities • Author original engineering questions that test deep conceptual understanding. Ensure questions are unambiguous, self-contained, and precisely defined., • Rate each question's difficulty: Medium (intro undergraduate), Hard (advanced undergraduate), or Expert (post-graduate and above)., • Provide 1 correct answer and 9 plausible but subtly incorrect alternatives that challenge expert-level solvers., • Write step-by-step Chain-of-Thought solutions with clear, concise intermediate steps in markdown format., • Supply 1–5 academic references per question from reputable sources such as peer-reviewed journals and university repositories. Must-Have • PhD or doctoral candidate in Engineering or a closely related field., • Master's degree considered for candidates with exceptional depth in a specific subdomain., • Strong command of graduate-level engineering principles, applied mathematics, and domain-specific standards., • Professional engineering licensure (PE) or industry experience is a strong plus., • Upload resume, • AI interview based on your resume

Job Description Quantitative Researcher — High Frequency Equities (US Markets, New York) Location: New York, HK, China Responsibilities • Analyze diverse datasets across US equity and futures markets to identify quantifiable trading edges and discover actionable alpha signals in high‑ and mid‑frequency domains., • Conduct end‑to‑end research including alpha factor mining, feature engineering, model construction, backtesting, and strategy optimization with realistic transaction cost and execution modeling., • Design and run robust backtests, walk‑forward validation, and stress tests to ensure signal stability and economic significance., • Collaborate with execution, engineering, and risk teams to translate research into production‑ready strategies and support live deployment/monitoring., • Bachelor's, Master's, or PhD in Statistics, Physics, Computer Science, Mathematics, or another quantitative field., • Proven hands‑on experience with high‑frequency US equity trading (experience with tick‑level data, microstructure, order book dynamics, and execution constraints is required)., • Proficiency in at least one programming language: Python (preferred), C++, C#, MATLAB, or R., • Strong data engineering and numerical skills for handling large tick‑level datasets and building scalable backtesting pipelines., • Ability to read and synthesize academic/technical English literature and rapidly learn new technical domains., • Competition awards (e.g., IMO/IPhO/ACM‑ICPC) or strong contest performance., • Publications in top‑tier peer‑reviewed journals or conferences., • Experience with low‑latency systems, co‑location, market data feeds, and execution optimization techniques., • Please submit your CV and a brief summary of relevant HF experience, including the markets/data you worked with, example signals or strategies developed, and any performance/production outcomes.

Job DescriptionAbout the Role We are seeking an exceptional quantitative researcher to lead our intraday equities alpha team. You will focus on discovering and modeling short-horizon statistical signals across large equity universes, leveraging high-frequency market data and cross-sectional relationships. This role is ideal for candidates with a strong background in signal research and a deep understanding of market microstructure. What You'll Do • Develop and test short-term alpha signals using high-frequency (tick-level and order book) data across global equity markets., • Analyze inter-symbol dynamics, liquidity patterns, and cross-sectional dependencies to identify transient inefficiencies and arbitrage opportunities., • Conduct rigorous backtesting and performance attribution across large baskets of equities in a fully systematic environment., • Collaborate with engineering and trading teams to deploy and monitor strategies in live production., • Continuously refine signal stability, robustness, and decay profiles across changing market regimes.What We Look For, • 5+ years of experience in alpha research or quantitative signal development, ideally in intraday or short-horizon equity strategies., • Deep understanding of market microstructure, order flow dynamics, and execution-related features that affect signal quality., • Strong programming skills in Python and/or C++, and fluency in working with large-scale high-frequency datasets., • Experience in cross-sectional modeling and statistical arbitrage frameworks across equities., • Advanced degree (MS/PhD) in a quantitative field such as mathematics, physics, statistics, computer science, or related disciplines.Nice to Have, • Experience with production-level alpha deployment in global equity markets (US, CN, APAC, EMEA)., • Familiarity with execution-aware signal design (slippage modeling, alpha decay, trade-to-book impact)., • Track record of successful signal ideas contributing to live PnL.Summary, • You'll work on short-horizon predictive modeling using high-frequency cross-sectional signals across equities. You won't manage execution or risk, but you'll work closely with teams who do. If you're passionate about alpha and fluent in market data, this role is for you. Pay Range: • Actual salary is commensurate with candidate's relevant years of experience, skillset, education and other qualifications. Base salay USD $125,000.00 - USD $500,000.00/Yr.

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government. Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI. About the Role A Lead Data Scientist is responsible for designing and implementing data-driven solutions to complex business problems. The role requires extensive experience in data analysis, agentic AI, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and collaborate with cross-functional teams. Responsibilities • Team Leadership: Lead a team of data scientists to develop innovative solutions to complex business problems. Mentor and develop the skills of junior data scientists and provide feedback and guidance to help them improve their work., • Collaboration: Collaborate with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers to develop and implement data-driven solutions., • Strategic Assessment: Assess the business needs of clients and identify areas where AI can be used to improve processes, reduce costs, or increase revenue., • Solution Design: Design and implement statistical models, machine learning algorithms, predictive analytics models, and agentic systems to solve business problems., • Communication: Communicate technical insights and recommendations to non-technical stakeholders in a clear and concise manner., • Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and artificial intelligence, and apply new technologies and techniques to solve business problems., • Pipeline Management: Responsible for developing, implementing, and managing end-to-end machine learning pipelines. This will involve building, deploying, and maintaining machine learning models, as well as ensuring data quality and system stability. Requirements for the Role, • Education: Bachelor's, Master's, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field., • Experience: 6+ years of total experience in Data Science, Machine Learning & Generative AI., • Cloud Computing: 4+ years of hands-on experience with AWS, including deep expertise in deploying models and managing compute environments., • IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX, • Agentic AI Tools: Experience with LangGraph, Google ADK or similar., • Agentic Architectures : Experience with advanced RAG & multi-agent systems., • Programming: Strong programming skills in languages such as Python, R, C++, and SQL., • Frameworks: Hands-on experience with ML frameworks, such as PyTorch or TensorFlow. XDOyWllq0r

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Mathematician Type: Contract Compensation: $25–$60/hour Location: Remote Commitment: 10+ hours/week Role Responsibilities • Author original math questions that test deep conceptual understanding. Ensure questions are unambiguous, self-contained, and precisely defined., • Rate each question's difficulty: Medium (intro undergraduate), Hard (advanced undergraduate), or Expert (post-graduate and above)., • Provide 1 correct answer and 9 plausible but subtly incorrect alternatives to challenge expert-level solvers., • Write step-by-step Chain-of-Thought solutions with clear, concise intermediate steps in markdown format., • Supply 1–5 academic references per question from reputable sources such as peer-reviewed journals and university repositories. Must-Have • PhD or doctoral candidate in Mathematics, Applied Mathematics, Statistics, or a closely related field., • Master's degree considered for candidates with exceptional depth in a specific subdomain., • Strong command of graduate-level mathematical concepts and formal proof writing., • Upload resume, • AI interview based on your resume

Job Description At HelloFresh, we want to change the way people eat forever by offering our customers high-quality food and recipes for different meal occasions. Over the past 10 years, we've seen this mission spread around the world and beyond our wildest dreams. Now, we are a global food solutions group and the world's leading meal kit company, active in 18 countries across 3 continents. So, how did we do it? Our weekly boxes full of exciting recipes and fresh ingredients have blossomed into a community of customers looking for delicious, healthy, and sustainable options. The HelloFresh Group now includes our core brand, HelloFresh, as well as: Green Chef, EveryPlate, Chefs Plate, Factor_, and Youfoodz. As an Applied Scientist on the Demand Forecasting team, you will help shape how HelloFresh predicts and plans customer demand across our US supply chain. Your work will sit at the intersection of data science, optimization, and operations. You’ll be building models that directly drive business-critical decisions from menu planning and procurement to fulfillment. You’ll partner closely with product, engineering, and operations teams to design, test, and deploy advanced forecasting and decision systems. You’ll explore and apply state-of-the-art machine learning and statistical techniques to improve forecast accuracy, quantify uncertainty, and enable better planning decisions. Beyond building models, you'll play a key role in translating complex scientific insights into scalable tools and strategies that enhance efficiency and reduce waste throughout the supply chain. You will… • Develop, prototype, and deploy forecasting models that capture complex demand patterns and constraints across multiple brands, products, and time horizons., • Build scalable data pipelines leveraging Databricks, Snowflake, and AWS., • Create mathematical optimization models and tools to solve practical business problems; roll them out., • Collaborate cross-functionally with procurement, planning, and operations teams to translate scientific work into measurable business outcomes., • Identify problems proactively, formulate and implement robust and data-driven solutions., • A hands-on problem solver with experience applying scientific methods to real-world operational challenges., • Skilled in Python and familiar with common machine learning and optimization techniques., • Experienced in data manipulation and analytics within cloud-based ecosystems., • Agile – you thrive in fast-paced and dynamic environments and are comfortable working autonomously, • Comfortable balancing scientific rigor with business pragmatism; able to communicate insights effectively to both technical and non-technical audiences., • A degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Operations Research, or a related discipline (Master’s or PhD preferred)., • 3+ years of experience applying machine learning, forecasting, or statistical modeling in an applied business setting., • 2+ years of experience building tools/applications in a high-level language, such as Python or Java., • Experience working with large, complex datasets using SQL and Python-based data ecosystems., • Competitive hourly rate, 401K company match that vests immediately upon participation, & team bonus opportunities, • Generous PTO and flexible attendance policy, • Comprehensive health and wellness benefits with options at $0 monthly, effective first day of employment, • Up to 85% discount on subscriptions to HelloFresh meal plans (HelloFresh, Green Chef, Everyplate, and Factor_), • Access to Employee Resource Groups that are open to all employees, including those pertaining to BIPOC, women, veterans, parents, and LGBTQ+ At HelloFresh, we embrace diversity and inclusion. We are an equal-opportunity employer and do not discriminate on the basis of an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived. As part of the Company’s commitment to equal employment opportunity, we provide reasonable accommodations, up to the point of undue hardship, to candidates at any stage, including to individuals with disabilities. We want to adapt our processes and create a safe space that welcomes everyone so please let us know how we can accommodate our process. In case you have any accessibility requirements you can share that with us in the application form. To learn more about what it's like working inside HelloFresh, follow us on Instagram and LinkedIn. HelloFresh is committed to the principles of equal employment opportunity and providing reasonable accommodations to candidates with disabilities. If you need an accommodation during the application process, please reach out to us at:

The Department of Mathematics invites applications for a tenure-track faculty position at the rank of Assistant Professor. The position is expected to begin July 1, 2026, contingent on final confirmation of funding. All candidates should have an outstanding record in research and be committed to excellence in teaching. Duties include research, department and university administration service, and teaching at the undergraduate and graduate level. PhD is required at the time of appointment. Candidates must have excellent scholarship and promise for future development. Candidates for assistant professor should have completed successful graduate training and are beginning a career of independent professional accomplishment. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Title: Math Adjunct Department: Mathematical Sciences Reports To: Chair Position Type: Faculty Position Summary: The Department has part-time adjunct positions available particularly for courses such as Pre-Calculus, Calculus, Differential Equations, and Statistics & Probability. Essential Functions: Functions include, but are not limited to, teaching assigned course(s), maintaining student attendance records, and holding regularly scheduled office hours. Additional Functions: If assigned to a coordinated course, must participate in common exam proctoring and grading. Essential Characteristics: Must abide by the university's core values which include excellence, integrity, civility, social responsibility, diversity and communication. Prerequisite Qualifications: M.S. degree in Mathematics or Statistics or related field required. Preferred Qualifications: PhD preferred. Prior teaching experience strongly preferred. Prior teaching experience at the collegiate level is a plus. At the university's discretion, the education and experience prerequisites may be excepted where the candidate can demonstrate to the satisfaction of the university and the SPHS Leadership Council, an equivalent combination of education and experience specifically preparing the candidate for success in the position. Bargaining Unit: AFT-UCAN Salary Information: In compliance with the NJ Pay Transparency Law, the rate for this position is $2668 per contact hour (USD). NJIT considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses or other items. FLSA: Exempt Part-Time Special Instructions to Applicants: Must have CV/Resume and cover letter attached. If available, please provide teaching evaluations with CV and cover letter using the "other documents" option to attach. Apply NowShare Save Job

The Department of Applied Physics and Applied Mathematics at Columbia University invites applications for an Associate Research Scientist position in theoretical condensed matter and materials physics, with an emphasis on the development of computational and analytical methods for strongly correlated electron systems. This position is part of a research program dedicated to advancing the Variational Discrete Action Theory (VDAT) - a novel variational approach to the quantum many-body problem. Candidates should have a strong background in theoretical/computational condensed matter and or materials physics, or related field. Experience with computational many-body physics is desired, including techniques such as the dynamical mean-field theory, quantum Monte-Carlo approaches, diagonalization approaches, etc. Strong candidates with related, but different, expertise will be considered. Programming experience is desirable. Strong communication skills (oral and written) are essential, and the ability to mentor students in a team environment is desirable. The position is initially for six months, possibly extending to four years. The position is available immediately and will remain open until it is filled. T Candidates must have a PhD in physics, materials science, applied math, chemistry, or a related field with a minimum of 2 years of relevant post-PhD experience. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Responsibilities: The Computational Biomarker Imaging Group (CBIG) has an open postdoctoral positions. CBIG's mission is to act as a translational catalyst between computational science and cancer imaging research. Work in our group focuses on developing innovative image analysis, machine learning, AI and data science methodologies for multimodality imaging, and also on incorporating such methods into clinically relevant applications. Most of our work to date has been on breast and lung cancer imaging, while more recently expanding more broadly in oncologic imaging and molecular imaging applications. A priority area is integrating imaging with genomic biomarkers towards integrated precision diagnostics for prevention and therapy for cancer. Applications focusing on radiomics and deep learning are also a priority. We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals. Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary research team. Salary range is from $75,000 - $85,000 The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Successful candidates should have, or be in the process of completing, a PhD (or equivalent) in Biomedical, Electrical or Computer Engineering, Computer and Information Science, Applied Mathematics, Statistics/Biostatistics, Bioinformatics, or related field. Ideal applicants should have a background on biomedical image analysis, computer vision, pattern recognition and/or machine learning. Experience with Bioinformatics is a plus. Proficiency in quantitative analytical methods and computer programming (e.g., Python, C/C ) is essential. Experience with medical image analysis (e.g., MRI, CT, X-ray, Ultrasound) and related statistical methods and software packages (e.g., ITK C/C libraries, R/SPSS) is desired (but not necessary). Experience with Deep Learning is also ideal (e.g., TensorFlow, Keras, PyTorch packages, etc.). Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Mercor is seeking STEM PhDs for a premier project with one of the world's top AI labs. You're a good fit if you: - Have a STEM PhD from a US, UK, Canadian, or European university in domains such as Mathematics, Biology, Chemistry, Physics, Computer Science, Statistics, Economics - Have high **at

Sr. Distinguished Applied Researcher Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is an individual contributor (IC) role driving strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected IC leader, you will guide and mentor a team of applied scientists and their managers without being a direct people leader. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. In this role, you will: * Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. * Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. * Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. * Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. * Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: * You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. * Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. * Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. * A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. * Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. * Has a deep understanding of the foundations of AI methodologies. * Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. * An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. * Experience in delivering libraries, platform level code or solution level code to existing products. * A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. * Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Key Responsibilities: * Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money. * Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. * Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. * Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. * Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Basic Qualifications: * PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research Preferred Qualifications: * PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields * LLM * PhD focus on NLP or Masters with 10 years of industrial NLP research experience * Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) * Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) * Has worked on an LLM (open source or commercial) that is currently available for use * Demonstrated ability to guide the technical direction of a large-scale model training team * Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens * Experience with common training optimization frameworks (deep speed, nemo) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $311,900 - $356,000 for Sr. Distinguished Applied Researcher Cambridge, MA: $343,100 - $391,600 for Sr. Distinguished Applied Researcher McLean, VA: $343,100 - $391,600 for Sr. Distinguished Applied Researcher New York, NY: $374,300 - $427,200 for Sr. Distinguished Applied Researcher San Francisco, CA: $374,300 - $427,200 for Sr. Distinguished Applied Researcher Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with t

Columbia Business School is seeking to hire one or more Staff Associates of research for the accounting division. The work will include quantitative and qualitative research and analysis involving the collection, coordination and management of information and data. This position provides an opportunity to gain experience in academic economics research and would be ideal preparation for a PhD program in accounting, finance, economics, or other related fields. This is a two-year position with a possible extension for a third year. The Staff Associate duties involve work in one or more of the following areas of research: accounting, finance, economics, and statistics. Specific duties include: • Collect, clean, and maintain datasets and databases. Extract and link data from multiple databases for analysis. Prepare detailed documentation., • Develop models and implement program code (STATA, Python, SQL, R, SAS, Matlab, etc.)., • Perform statistical analysis, including regression analysis and machine learning techniques., • Assist with data analysis and dissemination of findings through the preparation of reports, journal articles, presentations, web sites, and other research outlets., • Perform case-based research, including work with detailed primary documents. Applicants for Staff Associate position are expected to have the following: • Programming experience in STATA and/or SAS and/or R is required., • Additional programming experience in one or more of the following languages: Python, SQL, Matlab, and/or C++ is preferred., • Familiarity with statistical tools such as linear regression is required., • Familiarity with text parsing and analysis (natural language processing) and/or machine learning techniques is preferred., • Candidate must be organized and able to work on multiple projects simultaneously., • Up to two years of research experience in a research role as a research assistant during the academic year or a summer internship in a research lab or governmental institution. Columbia University is an Equal Opportunity/Affirmative Action employer. Women and minorities are especially encouraged to apply. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

The Department of Applied Physics and Applied Mathematics (APAM) at Columbia University in the City of New York invites applications for a limited-term Assistant Professor faculty position in the area of applied and computational mathematics. The position begins July 1, 2026 for a term of 3 years. Salary is competitive and the teaching load is relatively light. Basic responsibilities focus on teaching, research and service. A recent PhD earned in the last 3 years and no later than the start date of the appointment, and extraordinary promise in research, are both required. A broad array of research groups is active in the department, with current research encompassing applied and computational mathematics, and their application to many areas of physics, materials science, biology, earth science, as well as imaging and data science. There is a strong cohort of activities on applied and computational mathematics within the Fu Foundation School of Engineering and Applied Sciences and the affiliated Data Science Institute. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Impact: help shape the future of AI systems built to reason about data and analytics. A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus.