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Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. • Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements, • Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs), • Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows, • Deploy and configure AI models and agents within customer security and compliance boundaries, • Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation, • Architect multi-agent systems that orchestrate between different models, tools, and data sources, • Implement evaluation frameworks to measure agent performance and iterate toward business objectives, • Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement, • Create sophisticated prompt engineering strategies optimized for customer-specific domains and data, • Build and maintain prompt libraries, templates, and best practices for customer use cases, • Conduct systematic prompt experimentation and A/B testing to improve model outputs, • Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate, • Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts, • Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration, • Work closely with Scale's product and engineering teams to translate customer needs into product improvements, • Document technical architectures, integration patterns, and best practices, • Debug complex technical issues across the entire stack, from data pipelines to model outputs, • Rapidly prototype solutions to unblock customers and prove out new use cases, • Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems, • Identify opportunities for productization based on common customer patterns, • 5+ years of software engineering experience with 2+ yrs of Management experience with strong fundamentals in data structures, algorithms, and system design, • Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API), • Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure, • Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions, • Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures, • Experience building and deploying AI agents or autonomous systems in production, • Knowledge of vector databases and semantic search systems, • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines, • Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools, • Previous work in a devops, platform, or infra role, • Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role, • Domain expertise in verticals like finance, healthcare, government, or manufacturing For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly. Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn. We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$216,000—$270,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. 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 ___. 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.

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You'll Do: • Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers, • Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs), • Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs., • Deliver experiments at a high velocity and level of quality to engage our customers, • Work across the entire product lifecycle from conceptualization through production, • 4+ years of full-time engineering experience, post-graduation, • Experience scaling products at hyper growth startups, • Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies, • Proficient in Python or Javascript/Typescript, and SQL, • Experience with Kubernetes, • Experience with major cloud providers (AWS, Azure, GCP) 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 ___. 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.

Scale GP is building the infrastructure that makes enterprise AI seamless. We are looking for a Senior or Staff Infrastructure Engineer to act as a primary technical lead, engineering the 'paved road' for our knowledge retrieval and inference engines. You won't just be managing resources; you'll be defining the deployment standards for Agentic workflows at scale. Your mission is to bridge the gap between complex AI orchestration and world-class infrastructure, ensuring our platform remains the most reliable destination for enterprise agents The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus. You will architect and implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You'll Do: • Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers., • Use our own data and AI platform to analyze build and test logs and metrics to identify areas for improvement., • Define the architectural patterns for our multi-cloud infrastructure to support secure, reliable, and scalable Agentic workflows for enterprise customers., • Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection., • Collaborate with platform and product teams to develop and implement innovative infrastructure that scales to meet evolving needs., • Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale., • Lead the infrastructure roadmap with a strong focus on compliance, privacy, and security standards, including designing change management and data isolation strategies., • Own the development and maintenance of our best-in-class Agentic observability platform (logging, metrics, tracing, and analytics) to proactively ensure system health and enable rapid incident response., • Proven experience in a senior role, with 5+ years of full-time software engineering experience., • Deep understanding of modern infrastructure practices, including CI/CD, IaC (e.g., Terraform, Helm Charts), container orchestration (e.g., Kubernetes) and observability platforms (e.g., Datadog, Prometheus, Grafana)., • Extensive experience with at least one major cloud provider (AWS, Azure, or GCP)., • Strong knowledge of security and compliance in enterprise environments, with a focus on access management, data isolation, and customer-specific VPC setups., • Proficiency in Python or JavaScript/TypeScript, and SQL. 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 ___. 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.

___ Job Type Full-time Description Vector Solutions is looking for a Director of Revenue Insights & Analytics to join our team. Reporting to the VP of Revenue Strategy & Operations, you will serve as a strategic leader driving change across revenue-generating teams, finance and marketing through data, dashboards and reporting strategy. You will partner with cross functionally with Sales, Marketing, Customer Success, Finance and Growth team members to define and communicate key metrics to drive revenue. The ideal candidate will be a forward thinking, motivated, hands-on leader with a passion for data-driven analytics and proven ability to build scalable analytics systems and a track record of turning insights into revenue outcomes. What You'll Do • Own and continuously refine revenue forecasts, planning and performance across business segments utilizing historical data, market trends, and sales projections., • Own and iterate on scalable analytics systems, including custom dashboards and automated reporting frameworks to ensure GTM leaders have real-time visibility into performance and pipeline health in both CRM Analytics and core SFDC Lightning reporting., • Monitor performance against targets for new logos, renewals, cross sells and upsells and making necessary adjustments to achieve revenue goals., • Communicate effectively on KPIs and metrics for Sales, GTM, and CX teams, developing unified reporting standards and visualizations that empower leaders to act quickly and confidently., • Develop and strengthen relationships with internal departments and stakeholders ensuring effective cross-functional collaboration, aligning data strategy with business priorities to drive top-line growth., • Refine and expand upon current processes to automate tasks and reporting and improve data capture and utilization in business decisions., • Champion system and process enhancements that improve data integrity, speed to insight, and adoption of analytics tools across teams., • Work alongside GTM leadership to define marketing and sales goals, quotas, and territories, and provide insights and recommendations on campaign performance and trends., • Partner closely with Marketing Operations to link campaign analytics with revenue outcomes, attribution modeling, and ROI analysis., • Create and maintain capacity models, including headcount and territories by role based on KPIs, metrics, and pipeline goals., • Lead, mentor, and develop a team, fostering a culture of collaboration, accountability, and innovation., • Establish a vision for analytics excellence-developing talent, standardizing best practices, and driving adoption of a unified data strategy., • Act as the key architect and evangelist for revenue insights-owning the roadmap for analytics systems, integrations, and BI tools to enable scalable growth and decision-making., • Regularly present insights and recommendations to senior leadership, influencing strategic decisions related to revenue acceleration, customer lifecycle optimization, and go-to-market efficiency. Requirements, • Bachelor's degree in Business, Economics, Data Science, or related field; advanced degree preferred., • 10+ years of experience in analytics, business intelligence, or revenue operations, with at least 5 years in a leadership or director-level role supporting Sales, Marketing, or Customer Success organizations., • 4+ years' experience in Revenue Operations, ideally within a B2B SaaS environment., • Proven track record of building and scaling analytics systems and dashboards using tools such as CRM Analytics, Tableau, Power BI, Looker, or equivalent BI platforms., • Strong technical acumen in CRM and marketing automation platforms (Salesforce, HubSpot, Marketo, etc.), with a solid understanding of data integration, modeling, and pipeline management., • Deep experience in forecasting, pipeline analysis, and revenue performance management in a B2B SaaS or subscription-based environment., • Exceptional leadership and communication skills with the ability to translate data into clear, actionable strategies for executives and functional leaders., • Strong understanding of GTM motions, including sales productivity, marketing attribution, customer retention, and expansion analytics., • Experience leading teams of analysts and system developers to deliver scalable, automated insights solutions., • People leader with a passion for developing and guiding teams to deliver on results., • Demonstrated proficiency in Salesforce and Tableau or Power BI., • Excellent analytical skills; ability to analyze complex data sets, draw meaningful insights, and provide actionable recommendations to support sales decision-making, • High level of business acumen; proven ability to get to the heart of the request and present data and analytics to senior leadership and key stakeholders., • Friendly, open, and casual work environment, • Comprehensive benefits package effective the first of the month after hire, • Matching 401(k) retirement plan, • Healthy work-life balance with flexible work arrangements and generous time off, • Generous referral incentive program, • Tuition Reimbursement Program, • Pet Insurance, • OnePass Gym/Wellness Discount Program, • Calm Health-Employee Membership, • Company social events, • Employee Resource Groups, • Teamwork - Above all, we're a team. We give and value feedback. We support each other, respect each other and work together to accomplish our common goals and serve our customers. Once we make decisions, we align behind them as a team., • Customers First - Our customers' success is our success. They are why we are here. We work to earn the trust of our customers and always deliver on our commitments., • Make a Difference - It's not a job, it's a calling. We have passion for our mission, for our customers, for our work, and for sharing a fulfilling experience with our fellow team members., • Inclusiveness - Uniqueness is powerful. We support an environment of respect, belonging, and community that promotes a variety of perspectives and crucial conversations, leading to better outcomes., • Act Now - We act with urgency. The best time to get something important done is now. We don't wait and let perfection be the enemy of good., • Curiosity - We love a good challenge. We're scrappy, we stretch ourselves to be the best, ask questions, learn from our mistakes, and are dedicated to continually improving and growing. Compensation Disclaimer: The base salary range provided is a good-faith estimate at the time of posting. Actual pay may vary based on factors such as skills, qualifications, experience, and work location. Compensation will always comply with applicable state and local pay laws, including but not limited to those in California, Colorado, New York, and Washington. Salary Description 170K-190K + bonus

Scale AI is seeking a highly technical and strategic Staff / Senior Staff Machine Learning Engineer to act as the Tech Lead (TL) for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency. The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus. Technical Leadership & Vision • Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI's overall AI strategy and business goals., • Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities., • Core Agent Capabilities Development:, • Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises., • Data analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas., • Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base., • Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale., • Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth., • Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team., • Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions., • Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience., • 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment., • 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain., • Deep expertise in Generative AI and Large Language Models (LLMs)., • Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale., • Experience with large-scale distributed systems and real-time data processing., • Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field., • Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization., • Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms., • Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems., • Experience with vector databases and advanced retrieval techniques., • A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD)., • Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers. 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 ___. 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.

___ Description Vector Solutions is the leader in providing industry-focused SaaS solutions that connect content and technology. Vector's unique product set aims at training and learning management, continuing education (CE), compliance, workforce scheduling, safety management, and more. Our mission is to empower everyday heroes in the public, educational and commercial sectors to make safer, smarter, and better decisions. Vector Solutions is seeking a Sector Business Analyst Intern. This individual will support sector-level analysis through a mix of Excel-based data work and market research, with a focus on learning how to combine internal Salesforce data and external research to answer business questions and identify opportunities for improvement. What You'll Do • Support sector-level business analysis by combining internal Salesforce data with external market research to answer strategic business questions., • Conduct industry deep dives to identify areas of strength, gaps in performance, and competitive opportunities., • Analyze revenue, retention, and customer data (e.g., ACV, churn risk, sentiment, usage) to uncover trends and drivers of success across industries., • Build and manipulate Excel-based datasets to organize findings and generate actionable insights., • Synthesize data into clear, well-structured conclusions and present recommendations to support decision-making. Requirements • Must be entering your senior year in Fall 2026 pursuing a Bachelor's degree in a related field, • Can commit to a 10 week Summer Intern Program May 26th- July 31st, • Strong communication skills, both verbal and written, with a professional demeanor, • Highly motivated self-starter, • Ability to work collaboratively in a fast-paced, team-oriented environment, • Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint), • Friendly, open, and casual work environment, • Comprehensive, quality benefits package effective first of the month following your date of hire, • Tuition Reimbursement Program, • Matching 401(k) retirement plan, • Healthy work-life balance with flexible work arrangements and generous time off, • Generous referral incentive program, • Company social events, • Teamwork - Above all, we're a team. We give and value feedback. We support each other, respect each other and work together to accomplish our common goals and serve our customers. Once we make decisions, we align behind them as a team., • Customers First - Our customers' success is our success. They are why we are here. We work to earn the trust of our customers and always deliver on our commitments., • Make a Difference - It's not a job, it's a calling. We have passion for our mission, for our customers, for our work, and for sharing a fulfilling experience with our fellow team members., • Inclusiveness - Uniqueness is powerful. We support an environment of respect, belonging, and community that promotes a variety of perspectives and crucial conversations, leading to better outcomes., • Act Now - We act with urgency. The best time to get something important done is now. We don't wait and let perfection be the enemy of good., • Curiosity - We love a good challenge. We're scrappy, we stretch ourselves to be the best, ask questions, learn from our mistakes, and are dedicated to continually improving and growing. Vector Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender, race, color, religion, national origin, age, pregnancy, disability, genetic information, or status as a protected veteran. The base salary range provided is a good-faith estimate at the time of posting. Actual pay may vary based on factors such as skills, qualifications, experience, and work location. Compensation will always comply with applicable state and local pay laws, including but not limited to those in California, Colorado, New York, and Washington Salary Description $17-18/hour

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale - unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data - securing and protecting private information more effectively - Elastic's complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role: Elastic, the Search AI company, is looking for a high-energy Enterprise Account Executive to drive net-new revenue and expansion within strategic Enterprise accounts. You'll be the owner of a defined territory where you'll build your own pipeline, tell the Elastic Search AI story, and close complex, multi-stakeholder deals in a consumption-based model. This role sits at the intersection of sales execution, technical fluency, and cross-functional collaboration-and is critical to our growth in the Enterprise segment. What You Will Be Doing: • Own your territory & build pipeline: Develop and execute a proactive outbound cadence (email, call, social) that generates 50% of your booked opportunities., • Deep discovery & qualification: Uncover pain, business impact, budget, and decision criteria using frameworks like MEDDPICC so you chase only the highest-confidence deals., • Value storytelling & demos: Craft and deliver tailored narratives and live demos that map Elastic's Search, Observability, and Security capabilities to measurable business outcomes., • Mutual deal strategy & forecast accuracy: Collaborate with customers to build formal close plans and keep your CRM up-to-date, maintaining 90% forecast accuracy within 10%., • Executive negotiation & closing: Lead high-stakes contract and pricing discussions-defend your value, structure give/get trades, and land multi-year consumption commitments., • Domain & cloud acumen: Position Elastic as the Search AI platform of choice by speaking fluently about cloud economics, usage-based pricing, and modern data architectures., • Cross-functional partnership: Work hand-in-glove with Solutions Architects, Customer Success, Marketing, and RevOps to accelerate deals and drive exceptional customer outcomes. What You Bring: • Proven SaaS quota-carrying success: 5+ years closing complex Enterprise deals, consistently overachieving targets in a consumption-based or usage-model environment., • Expert discovery & qualification skills: Demonstrated ability to apply MEDDPICC or equivalent frameworks to drive disciplined pipeline and eliminate low-probability deals., • Compelling value storytellers: Track record of delivering executive-level presentations and demos that tie product capabilities to real dollars saved, revenue gained, or risk mitigated., • Strong negotiation chops: History of landing multi-year, high-ACV contracts while protecting margin and securing executive stakeholder buy-in., • Technical & cloud fluency: Comfortable discussing a broad range of technical topics including observability, security, vector/traditional search, and cloud cost optimization., • Collaborative mindset & coachability: A learner who partners effectively with internal teams, incorporates feedback, and embodies Elastic's values of community and openness., • Open Source enthusiasm: Genuine appreciation for open-source communities and the Elastic model-bonus if you've sold or advocated in an OSS context. Bonus Points: • Prior experience at an open-source or developer-centric infrastructure company., • Familiarity with observability (logs, metrics, traces) or security analytics (SIEM/XDR) use cases. If you're driven to build your own pipeline, master complex deal cycles, and help customers unlock the power of Search AI, we'd love to talk. Apply today! Additional Information - We Take Care of Our People: As a distributed company, diversity drives our identity. Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do. • Competitive pay based on the work you do here and not your previous salary, • Health coverage for you and your family in many locations, • Ability to craft your calendar with flexible locations and schedules for many roles, • Generous number of vacation days each year, • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service, • Up to 40 hours each year to use toward volunteer projects you love, • Embracing parenthood with a minimum of 16 weeks of parental leave Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email ___. We will reply to your request within 24 business hours of submission. Applicants have rights under Federal Employment Laws and can view the following posters linked below: Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries' export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic. Please see ___ for our Privacy Statement. Compensation for this role is in the form of base salary plus a variable component, that together comprise the On-Target Earnings (OTE). On-Target Earnings (OTE) are based on a 50/50 pay mix (base salary / target variable). The typical starting OTE range for new hires in this role is listed below. This range represents the lowest to highest OTE we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's position within the OTE range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $113,300-$175,000 USD The typical starting Target Variable range for this role is: $113,200-$175,000 USD The typical starting On-Target Earnings (OTE) range for this role is: $226,500-$350,000 USD

___ Job Type Internship Description Vector Solutions is the leader in providing industry-focused SaaS solutions that connect content and technology. Vector's unique product set aims at training and learning management, continuing education (CE), compliance, workforce scheduling, safety management, and more. Our mission is to empower everyday heroes in the public, educational and commercial sectors to make safer, smarter, and better decisions. The Commercial Sector partners with companies and organizations across highly regulated industries, including AEC, Industrial Manufacturing, OSHA-regulated environments, and other commercially accredited sectors. Our team ensures that training solutions align with industry standards, accreditation requirements, and evolving regulatory expectations. We are seeking a motivated and detail-oriented Commercial Program Intern to support subject matter expert (SME) recruiting, accreditation research, and commercial reporting initiatives. This role offers hands-on exposure to commercial operations, regulatory research, and cross-functional program execution. The ideal candidate is analytical, proactive, and interested in working within regulated industries where compliance and operational excellence drive business growth. What You'll Do SME Recruiting & Pipeline Management • Identify and research potential Subject Matter Experts (SMEs) aligned to sector needs, • Conduct professional outreach via LinkedIn and email, • Screen candidates to evaluate qualifications and industry alignment, • Schedule and coordinate qualification calls, • Support contract coordination and documentation tracking, • Research industry and association-specific accreditation requirements, • Track regulatory updates and renewal timelines, • Support documentation preparation for accreditation submissions, • Coordinate with Product and Content teams to ensure alignment with accreditation standards, • Pull and analyze LMS completion data and program metrics, • Track accreditation-related revenue and performance indicators, • Support SME pipeline reporting, • Build and maintain reports and dashboards in Excel, • Assist with Salesforce data management and reporting, • Assist with cross-functional coordination across Commercial, Product, and Content teams, • Support process documentation and workflow improvements, • Contribute to special projects and other duties as assigned Requirements • Must be entering your senior year in Fall 2026 pursuing a Bachelor's degree in Business, Data Analytics, Finance, Public Health, Criminal Justice, Industrial Management, Compliance/Regulatory Studies, Emergency Management, or a related field, • Can commit to a 10 week Summer Intern Program May 26th- July 31st, • Interest in regulated industries such as AEC, Industrial Manufacturing, OSHA-regulated environments, or other commercially accredited sectors, • Strong written and verbal communication skills, • High attention to detail and strong organizational abilities, • Comfortable conducting professional outreach and external communication, • Analytical mindset with proficiency in Microsoft Excel (pivot tables, formulas preferred), • Familiarity with Salesforce or CRM systems preferred, • Ability to manage multiple priorities in a fast-paced environment, • Friendly, open, and casual work environment, • Comprehensive, quality benefits package effective first of the month following your date of hire, • Tuition Reimbursement Program, • Matching 401(k) retirement plan, • Healthy work-life balance with flexible work arrangements and generous time off, • Generous referral incentive program, • Company social events, • Teamwork - Above all, we're a team. We give and value feedback. We support each other, respect each other and work together to accomplish our common goals and serve our customers. Once we make decisions, we align behind them as a team., • Customers First - Our customers' success is our success. They are why we are here. We work to earn the trust of our customers and always deliver on our commitments., • Make a Difference - It's not a job, it's a calling. We have passion for our mission, for our customers, for our work, and for sharing a fulfilling experience with our fellow team members., • Inclusiveness - Uniqueness is powerful. We support an environment of respect, belonging, and community that promotes a variety of perspectives and crucial conversations, leading to better outcomes., • Act Now - We act with urgency. The best time to get something important done is now. We don't wait and let perfection be the enemy of good., • Curiosity - We love a good challenge. We're scrappy, we stretch ourselves to be the best, ask questions, learn from our mistakes, and are dedicated to continually improving and growing. Vector Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender, race, color, religion, national origin, age, pregnancy, disability, genetic information, or status as a protected veteran. The base salary range provided is a good-faith estimate at the time of posting. Actual pay may vary based on factors such as skills, qualifications, experience, and work location. Compensation will always comply with applicable state and local pay laws, including but not limited to those in California, Colorado, New York, and Washington Salary Description $17.00 - 18.00 per hour

Description Our Culture & Team We're not just building AI-we're building human-in-the-loop solutions within a collaborative, patient first environment: • Pre-sales & Strategic Advisory, • Collaborate with commercial advisory consulting teams to identify new opportunities, tailor solutions to client needs, and accelerate adoption of our data products., • Support pre-sales activities, including RFP responses, solution demos, stakeholder workshops, and technical presentations to prospects and existing clients., • Present architectural strategies, tenets and product/architecture roadmaps to senior pharmaceutical executives, aligning solutions with budgetary constraints, business and commercial goals., • Develop data architecture designs, data governance/ data architecture frameworks, technical approaches, technical scope and partner with engineers on building accelerators, MVPs and demos., • Solution Architecture & Design, • Define end to end architecture for agentic AI systems (planning, memory, reasoning, multi-agent orchestration), • Integrate with existing pharma platforms: EHRs, CRMs, clinical trial systems, patient portals, ensuring compliance with standards (FHIR, GxP, HIPAA, FAIR), • Establish guardrails, escalation pathways, observability, and LLMOps/AgenticOps best practices, • Technical Leadership & Implementation, • Prototype and oversee design, build and deployment of agentic AI pilots (e.g. Personalized Patient Outreach, Medication Adherence & Side Effect Management, Prediction Model for disease progression), • Collaborate with cross-functional teams-product, engineering, MLOps-to operationalize data pipelines, microservices, and agent orchestration layers., • Ensure robust MLOps pipelines with model monitoring, drift detection, and responsible AI governance., • Client Engagement & Thought Leadership, • Serve as trusted technical advisor to pharma stakeholders (VP, SVP Digital Health, Patient Engagement) during pre- and post-sales., • Present architecture blueprints, ROI frameworks, risk assessments, and compliance strategies., • Capture feedback and collaborate with Life Sciences Commercial teams (i.e. Value & Access, Sales Operations, Brand Strategy, Digital Health, Patient Services) to evolve scalable agentic solutions.QualificationsRequired, • 7+ years as a Solution Architect/Consultant creating AI-powered systems, with 3+ years experience in generative agentic AI., • 5+ years in healthcare or pharma, implementing enterprise systems (EHR, clinical workflows, patient applications)., • 3+ years Consulting Experience, • 3+ years carrying a minimum of $1 Million Sales Quota, • Strong AI architecture & deployment know-how:, • Microservices, REST APIs, CI/CD data pipelines, cloud platforms, • MCP, RAG, AgentDNS, A2A Protocol, AI workflow automation, AI Memory Management, LLM Evaluation & Observability, Autonomous Planning & Reasoning, Custom Embeddings & Vector Search, • Skilled in Python, prompt engineering, LLM integration, and tool-based agent frameworks (e.g. LangChain, Semantic Kernel), • Expertise in standards: HIPAA, FHIR/HL7, GxP, FAIR.Preferred, • Hands-on experience with agentic frameworks and multi-agent architectures, • Exposure to MLOps/AgenticOps for production LLM systems., • Background with patient engagement tools or digital companion deployments, • Pharma domain expertise: clinical trials, pharmacovigilance, patient support services., • Outstanding communicator-able to engage C-level pharma executives. The annual base salary for this position ranges from $229,000 to $270,000. The base salary range represents the anticipated low and high of the Syneos Health range for this position. Actual salary will vary based on various factors such as the candidate's qualifications, skills, competencies, and proficiency for the role. In addition, some positions may include eligibility to earn commissions/bonus based on company and / or individual performance. At Syneos Health, we are dedicated to building a diverse, inclusive and authentic workplace. If your past experience doesn't align perfectly, we encourage you to apply anyway. At times, we will consider transferable skills from previous roles. We also encourage you to join our ___ to stay connected to additional career opportunities. Why Syneos Health? Here, you're a part of the big picture. You will collaborate with colleagues across clinical and commercial disciplines to guide premarket development through post-market commercial strategy. Every project is a chance to solve a new challenge, learn from your colleagues, and advance your career. The diversification and breadth of our new and existing partnerships create a multitude of career paths and employment opportunities. Join our game-changing, global company dedicated to creating better, smarter, faster ways to get biopharmaceutical therapies to patients. Experience the thrill of knowing that your everyday efforts are contributing to improving patients' lives around the world. Work Here Matters Everywhere | How are you inspired to change lives? Syneos Health companies are affirmative action/equal opportunity employers (Minorities/Females/Veterans/Disabled) Syneos Health has a voluntary COVID-19 vaccination policy. We strongly encourage all employees to be fully vaccinated. Additionally, certain local governments or Syneos Health customers may have vaccine requirements that apply to some of our employees. These employees are required to submit proof of vaccination to Syneos Health and maintain compliance with these requirements. At Syneos Health, we believe in providing an environment and culture in which Our People can thrive, develop and advance. We reward and recognize our people by providing valuable benefits and a quality-of-life balance. The benefits for this position will include a competitive compensation package, Health benefits to include Medical, Dental and Vision, Company match 401k, flexible paid time off (PTO) and sick time. Because certain states and municipalities have regulated paid sick time requirements, eligibility for paid sick time may vary depending on where you work. Syneos Health complies with all applicable federal, state, and municipal paid sick time requirements.

The Columbia Center on Sustainable Investment (CCSI) is seeking an Associate Research Scholar to advance its applied research, policy, and advisory work on integrated energy systems planning and finance. This role sits at the frontier of a rapidly evolving and increasingly integrated energy sector, where electrification, digitalization, e-mobility, urbanization, and emerging-market growth are transforming the operational logic and investment requirements of energy systems around the world. The position will engage directly with these dynamics, examining how system design, planning, and investment frameworks can optimize the integration of digital and physical infrastructure to support climate and development goals. This position will support the design and implementation of system-level strategies for low-carbon, affordable, and resilient energy transitions linking generation, grid infrastructure, and emerging load centers such as industrial corridors, data hubs, and clean-fuel value chains. This will include contributions to the development of integrated modelling frameworks, investment and financing roadmaps, and institutional and regulatory strategies that enable countries and regions to achieve net-zero, competitive, and inclusive growth. The position will bridge technical systems analysis with institutional and financial innovation to translate scenario-modelling outputs into investible transition pathways aligned with emerging global norms in climate finance, industrial policy, and digital infrastructure. This is a highly interdisciplinary position spanning energy systems analysis, sustainable finance, and public policy, and requires intellectual curiosity, creativity, and a pragmatic commitment to translating research into actionable solutions. This role will initially contribute to CCSI's work under the ASEAN Regional Integrated Energy System (ARIES) project, supporting the design of regional pathways, financing frameworks, and institutional mechanisms for coordinated energy system transformation across Southeast Asia. Key Responsibilities The Associate Research Scholar will contribute to CCSI's research and advisory initiatives through a combination of the following responsibilities, depending on evolving program needs and the individual's expertise: • Conduct interdisciplinary research on the planning, optimization, and financing of integrated energy systems, including cross-border grids, clean fuels, storage, and emerging industrial and digital loads., • Contribute to the design, development, and interpretation of energy system and macroeconomic models to identify least-cost and net-zero-consistent transition pathways, and to link those results / modelling outputs to investment and financing requirements., • Support the development of advanced multi-vector modelling frameworks that couple energy, water, and digital infrastructure, drawing on the latest approaches in integrated systems planning, electrotech deployment, and demand flexibility., • Analyze policy, regulatory, and market design options that enhance the affordability, security, and sustainability of energy systems across borders and sectors., • Support the development of financing and investment frameworks, including analysis of risk allocation, blended finance instruments, guarantees, sovereign and sub-sovereign borrowing, export credit agency (ECA) participation, and credit rating methodologies relevant to large-scale clean energy and infrastructure investment., • Conduct or contribute to research on cost-of-capital determinants, capital market access for emerging economies, and the design of mechanisms that can lower financing costs for public and private actors., • Explore and assess the role of regional and national financial institutions, development banks, and catalytic funds in mobilizing investment for integrated energy systems., • Engage with governments, regional institutions, utilities, development banks, investors, ECAs, and rating agencies to co-develop practical strategies for affordable and scalable financing of energy transitions., • Organize and facilitate consultations, workshops, and training programs to strengthen institutional and financial capacity for integrated system planning and implementation., • Collaborate on multi-stakeholder projects that bridge technical modeling, institutional reform, and financial innovation, including national and regional roadmaps for energy system transformation., • Draft and co-author research papers, policy briefs, roadmaps, and reports, synthesizing technical, financial, and institutional insights into clear and actionable recommendations., • Contribute to strategic outreach, communication, and knowledge-sharing efforts, ensuring that CCSI's research informs policy dialogues on sustainable infrastructure, energy integration, and reform of global financial architecture. The most important quality for this position is the ability and desire to think ambitiously, creatively, and pragmatically, and to bridge disciplines in pursuit of actionable, system-level solutions. Ideal candidates are self-motivated, intellectually curious, and collaborative, able to connect technical, financial, and policy insights into coherent strategies that shape real-world outcomes. In addition, the following minimum qualifications are required: • PhD, SJD, JD, LLM, or Master's degree with significant research experience in one or more of the following fields: energy systems, economics, sustainable finance, engineering, law, or public policy., • Demonstrated ability to conduct and synthesize interdisciplinary research across technical, economic, and institutional dimensions., • Strong analytical and writing skills, with the ability to translate complex concepts into actionable recommendations., • Familiarity with energy systems modeling, infrastructure planning, industrial decarbonization, or climate finance mechanisms (e.g., blended finance, guarantees, or sovereign credit structures)., • Demonstrated understanding of macroeconomic and systems-level implications of the current power and digital infrastructure nexus, • Experience working with or advising governments, utilities, multilateral institutions, or investors on energy, infrastructure, or finance issues., • Willingness to learn, adapt, and engage across diverse disciplines and stakeholder groups., • Regional experience in emerging markets preferred. Ultimately, the role contributes to a new generation of energy-system scholarship and practice that links digital transformation, electrification, and climate finance into coherent investment strategies. The Associate Research Scholar will engage with partners across government, industry, and finance to align technical insights with the institutional and capital architectures required for real-economy transitions that are affordable and effective. The search will remain open for at least 30 days after the advertisement appears and will continue until the position is filled. Appointments are made on a fiscal year basis and are eligible for renewal each July 1, contingent upon performance and funding. Columbia University benefits accompany this Officer of Reserch appointment. 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: Overview: We don't simply hire employees. We invest in them. When you work at Chatham, we empower you - offering professional development opportunities to help you grow in your career, no matter if you've been here for five months or 15 years. Chatham has worked hard to create a distinct work environment that values people, teamwork, integrity, and client service. You will have immediate opportunities to partner with talented subject matter experts, work on complex projects, and contribute to the value Chatham delivers every day. Chatham Financial is looking for an AI Solutions Engineer to design, build, and deploy custom AI solutions that address high-value business workflows. This is a hybrid technologist and trusted advisor role.You'llwork closely with stakeholders to understand operational challenges and build AI-powered solutions that create measurable value.You'llown problems end-to-end-from discovery through production. This is a hybrid technologist and trusted advisor role.You'llembedwith client teams, understand their operational challenges, and build AI-powered solutions that create measurable value. Think startup CTO meets management consultant-you'llownproblems end-to-end. What You'll Do: Client Engagement * Work directly with private equity firms, real estate investors, and capital markets clients to understand their workflows andidentifyAI opportunities * Lead discovery conversations to uncover pain points and scope solutions * Present recommendations to both technical and executive stakeholders Solution Design & Architecture * Architect custom AI solutions including workflow automation, data extraction, intelligent reporting, and AI agents * Evaluate when to use LLMs vs. traditional ML vs. rule-based approaches * Design systems that integrate with existing client infrastructure Hands-On Building * Write production code-Python, modern web frameworks, LLM integrations (OpenAI, Anthropic, etc.) * Build RAG systems, agentic workflows, and custom AI applications * Own the full stack from data ingestion to user interface Rapid Prototyping * Build working prototypes in days/weeks, not months * Validate value quickly with real users and real data * Iterate based on feedback and measured outcomes Production Deployment * Take solutions from prototype to production * Ensure reliability, security, and maintainability * Support ongoing optimization and enhancement Contributors to your success: * 7+ years of software engineering experience, ideally with client-facing or consulting exposure * Strong programming skills in Python; experience with TypeScript/JavaScript a plus * Hands-on experience building with LLMs (GPT, Claude, etc.)-RAG, prompt engineering, fine-tuning, or agentic systems * Experience taking AI/ML projects from prototype to production * Excellent communication skills-can explain technical concepts to executives and collaborate with non-technical stakeholders * Comfortable with ambiguity-can scope problems, make decisions, and own outcomes end-to-end * Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent experience * Experience in financial services, private equity, or real estate * Background at a startup (especially as early engineer) or consulting firm * Experience with data pipelines, ETL, and working with messy enterprise data * Familiarity with cloud platforms (AWS, Azure, GCP) * Experience with vector databases, embeddings, and semantic search About Chatham Financial: Chatham Financial is the largest independent financial risk management advisory and technology firm. A leader in debt and derivative solutions, Chatham provides clients with access to in-depth knowledge, innovative tools, and an incomparable team of over 700 employees to help mitigate risks associated with interest rate, foreign currency, and commodity exposures. Founded in 1991, Chatham serves more than 3,500 companies across a wide range of industries - handling over $1 trillion in transaction volume annually and helping businesses maximize their value in the capital markets, every day. To learn more, visit___. Chatham Financial is an equal opportunity employer.

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. • Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements, • Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs), • Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows, • Deploy and configure AI models and agents within customer security and compliance boundaries, • Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation, • Architect multi-agent systems that orchestrate between different models, tools, and data sources, • Implement evaluation frameworks to measure agent performance and iterate toward business objectives, • Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement, • Create sophisticated prompt engineering strategies optimized for customer-specific domains and data, • Build and maintain prompt libraries, templates, and best practices for customer use cases, • Conduct systematic prompt experimentation and A/B testing to improve model outputs, • Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate, • Serve as the primary technical point of contact for strategic enterprise accounts, • Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration, • Provide technical training and knowledge transfer to customer teams, • Work closely with Scale's product and engineering teams to translate customer needs into product improvements, • Document technical architectures, integration patterns, and best practices, • Debug complex technical issues across the entire stack, from data pipelines to model outputs, • Rapidly prototype solutions to unblock customers and prove out new use cases, • Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems, • Identify opportunities for productization based on common customer patterns, • 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design, • Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API), • Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure, • Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions, • Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures, • Experience building and deploying AI agents or autonomous systems in production, • Knowledge of vector databases and semantic search systems, • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines, • Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools, • Previous work in a devops, platform, or infra role, • Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role, • Domain expertise in verticals like finance, healthcare, government, or manufacturing For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly. Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn. We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$179,400—$224,250 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. 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 ___. 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.

Job Description Location: New York, NY Our client is a distinguished provider of legal services on a global scale. As an Innovation AI Developer, you will serve as a key member of the client’s Innovation Engineering team, responsible for designing and implementing intelligent, secure, and scalable AI applications to enhance the delivery of legal services and optimize business operations. In this capacity, you will collaborate closely with attorneys, business leaders, data scientists, and infrastructure teams to translate complex legal and operational needs into effective AI solutions with measurable outcomes. You will be involved in the entire AI lifecycle—from initial use case identification through production deployment and system monitoring—utilizing large language models (LLMs), retrieval-augmented generation (RAG), traditional machine learning approaches, and modern cloud architectures to advance efficiency, quality, and informed decision-making. This position offers the opportunity to develop enterprise-level AI capabilities at one of the world’s premier law firms, operating at the forefront of advanced engineering and impactful legal practice. The firm is committed to upholding rigorous performance standards and fostering a culture oriented toward growth. Individuals demonstrating initiative and dedication will be afforded opportunities for increased responsibilities and long-term career advancement within the organization. Desired Qualifications and Experience: · Bachelor’s degree in computer science or a related field preferred. · 7+ years of experience in professional services, legal, or technical environments, with demonstrated hands-on experience building and deploying AI applications. · AI Engineering Expertise – Strong Python development skills and experience designing and implementing RAG pipelines, working with vector databases (e.g., Pinecone), and building AI agents and multi-service AI architectures—particularly within Azure environments. · Cloud & DevOps Proficiency – Familiarity with Azure services (e.g., Cognitive Search, Cosmos DB, AI Studio), as well as Docker, Kubernetes, and CI/CD practices that support scalable, production-ready deployments. · Experience designing and maintaining LLM evaluation frameworks (e.g., Promptfoo, OpenAI Evals, LangSmith) and integrating structured and unstructured data sources into AI systems. · Experience operating within environments that require strict adherence to security, privacy, and governance standards for sensitive data. · Business Acumen & Communication – Proven ability to conduct stakeholder discovery, quantify return on investment (ROI), and translate ambiguous challenges into clearly defined AI requirements. · Strong communication skills with the ability to explain complex technical concepts to non-technical audiences. · Legal Domain Exposure (Preferred) – Experience supporting legal use cases such as due diligence, contract review, or legal research, and prior law firm experience. Summary of Responsibilities: · AI Solution Architecture & Development – Collaborate with legal and business stakeholders to identify high-value AI use cases, define measurable success criteria (e.g., efficiency, quality, risk reduction), and architect scalable solutions using Python and modern AI frameworks such as OpenAI, Azure OpenAI, Hugging Face, LangChain, and LangFlow. · Retrieval-Augmented Generation (RAG) & Intelligent Systems – Design, build, and maintain RAG pipelines using vector databases and knowledge graph solutions. Develop AI agents that automate multi-step workflows and enable sophisticated task orchestration. · Create reusable libraries, patterns, and documentation that support long-term innovation and maintainability across the firm’s AI ecosystem. · Design and maintain LLM evaluation frameworks to measure accuracy, robustness, safety, and alignment to use-case objectives. Ensure AI systems meet firm security, privacy, and governance standards. · Support continuous integration and continuous delivery (CI/CD) workflows, containerization (Docker), and orchestration (Kubernetes) to ensure production readiness. Partner with infrastructure and security teams to support hybrid cloud and on-premise deployments in sensitive data environments. · Serve as a subject matter resource for attorneys and business teams, advising on prompt engineering, model selection, and architecture decisions. Support pilot implementations, user training, and feedback loops to drive adoption and measurable impact. · Evaluate new tools, open-source libraries, and vendor platforms to inform firm AI strategy. Contribute to internal education and thought leadership on AI best practices. How to Apply: Our client has hired us to help facilitate the initial interview and recruiting process. Please attach your current version of your resume and make sure you complete our initial pre-screening questions that will be used for determining which applicants will be considered at this time. Thank you for your interest. Company DescriptionWe Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!We Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!

Job Description Position: Data Engineer Location: NYCNY/Atlanta GA (In-Person Interview) Duration: 12 Months Need locals to NY or GA with local DL/State ID W2 Only - Face to Face Interview Skills and Responsibilities: Design, develop, and optimize ETL pipelines using technologies such as Snowflake, Hadoop, Kafka,and distributed data systems, including real-time streaming and high-volumedata processing. Work across the full SDLCrequirements, design, coding, testing, deploymentwithstrong expertise in SQL,database design, Linux-based development, and distributed computing principles. Build and maintain data frameworks, dashboards, and analyticspipelines to deliver actionable business insights while ensuring performance,scalability, and reliability. Develop solutions using Python,Docker, Kubernetes, Bash, PowerShell, SQL/NoSQL/vector databases, and cloudplatforms such as AWS, Azure, GCP, or OCI.

Job DescriptionWe are seeking a skilled and motivated Data/AI Cloud Engineer to join our team! In this role, you will play a key part in implementing AWS data and AI/ML services, building ETL/ELT pipelines, and developing intelligent data solutions that empower our customers to derive meaningful insights from their data. You will collaborate closely with Cloud Architects and senior technical team members to design and deliver high-quality, scalable solutions — spanning data engineering, machine learning infrastructure, and AI-driven applications — aligned with customer needs. Responsibilities:· Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR· Creating and maintaining data extraction, transformation, and loading processes· Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB· Implementing data lakes using S3 and related AWS services· Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude· Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases· Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex· Writing and testing SQL queries and stored procedures· Documenting technical solutions and providing knowledge transfer to customers· Supporting the implementation of data governance and security controls· Troubleshooting and resolving issues with data pipelines and AI services· Participating in code reviews and implementing feedback· Assisting with proof-of-concept implementations for customer engagements Top candidates will have the following:· Technical familiarity with AWS data and AI/ML services and modern data engineering practices· Hands-on experience with ETL/ELT processes and data transformation· Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks· Ability to write and optimize SQL queries across various database platforms· Knowledge of data modeling concepts and best practices· Strong analytical and problem-solving skills· Eagerness to learn new technologies and keep up with cloud and AI innovations· Excellent communication skills with the ability to explain technical concepts clearly· Attention to detail and commitment to solution quality· Collaborative mindset with strong teamwork capabilities· Experience or interest in automation and infrastructure as code Required Experience for the Role:· Must have 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development· Must have 2+ years of hands-on AWS experience with production deployments· Must have 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)· Must have a proven track record delivering production AI applications from concept to deployment· Must have strong understanding of software engineering best practices (version control, testing, code review, documentation)· Must have experience working in agile/scrum environments with distributed teams· Must have excellent problem-solving skills and ability to work independently with minimal supervision· Must have strong written and verbal communication skills for client-facing interactions The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate’s professional experience, key skills, and education/training. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Who we’re looking for… Role: Senior Full Stack Engineer Team: Engineering Reports To: Head of Engineering Location: Knit’s NYC office (Hybrid) Operating hours: Monday - Friday 9am - 5pm EST. Travel: This role will occasionally be expected to travel for in-person internal working sessions, and our once per year US All Team Summit. [To be less than 15%] A little about us… Knit is building the agentic AI platform that helps enterprise brands run end‑to‑end consumer research. We orchestrate specialized AI agents for surveys, data collection, analysis, and reporting, delivering decision-grade insights to Fortune 1000 brands in hours, not weeks. In under two years, we’ve partnered with 50+ leading enterprise brands, including Amazon, Mars, NASCAR, JBL, ESPN, and Paramount. Knit has grown 500% in the last 12 months and raised $30.6M to date, including a $16.1M Series A in July 2025. Here are example case studies that demonstrate the value of our platform. A product demo can be found here. Overview We’re building our foundational NYC engineering team from scratch and looking for exceptional builders who are resourceful, deeply technical, and thrive in high-ownership environments. As one of the first in-house engineers, you’ll shape the core of our platform and the culture of a team that will scale to 20+ over the next 18 months. You’ll build and orchestrate AI agents, pioneer new UX paradigms, and tackle some of the hardest problems in applied AI with autonomy and end-to-end ownership. Business Impact | What you will own… • Own 0→1 and 1→N features across the stack, from design docs to building high-throughput data pipelines and scalable FastAPI services., • Architect and own the core agent orchestration engine, designing complex, multi‑agent LLM workflows (routing, tool‑use, memory, evaluation) with deterministic fallbacks, guardrails, and auditable actions required by enterprise users., • Build AI‑native, human‑in‑the‑loop UIs. Craft React/Next.js interfaces that let users collaborate safely with agents, with transparency and explainability by design., • Develop the "factory for the factory". Build our experimentation platform: CI/CD for prompts and agents, offline/online evals, drift detection, safety layers, and rollout controls., • Ship fast, safely. You’ll instrument everything for reliability, write concise design docs, add robust tests, and build dashboards and alerts for features you launch., • Partner cross‑functionally with Product, AI, Design, CS; talk to customers and SMEs, and turn ambiguous problems into shipped product., • Obsess over performance, optimizing for latency across the system: caching, model selection, distillation, batching, vector search, and infrastructure efficiency (GPU/CPU)., • Operate what you build. This includes on‑call ownership, leading incident response, and driving learning through blameless postmortems.Our Stack, • Frontend: React, Next.js, • Backend: Python, FastAPI, • Data/ML: MongoDB, S3, Redis; Pinecone, • Infra: AWS, Docker, Kubernetes; CI/CD with GitHub Actions., • Messaging: SQS; event‑driven pipelines.This role is for you if..., • You’re a 0 → 1 builder who thrives in ambiguity and has shipped products from scratch at a startup or in a hyper-growth phase. You've seen both - early-stage hustle and later-stage scale and know how to build for it., • You’re a systems thinker with deep technical chops: you design clear architectures and write clean, tested Python and TypeScript., • You think like an owner: you spot problems, propose solutions, and build them without waiting for perfect specs. Your impact is measured in business outcomes., • You use AI as leverage. Tools like Cursor, Copilot, or Claude Code are integral to your workflow, helping you ship faster while maintaining a high standard for correctness., • You believe speed and quality aren’t opposites and can articulate the tradeoffs you make., • You communicate crisply. You share your ideas effectively and thrive in tight feedback loops with product, design, and customers., • You’ve got grit: hard problems energize you, context switching doesn’t scare you, and you’re comfortable deleting code.This role is NOT for you if..., • You see a hard line between "frontend," "backend," and "product.", • You are uncomfortable with ambiguity, rapid context-switching, and dynamic priorities., • Experience with LLM/agent systems, evals, and prompt tooling; RAG, embeddings, vector dbs., • Deep knowledge of event‑driven systems, streaming, and workflow engines., • Expertise in observability (OpenTelemetry/Prometheus/Datadog), feature flagging, or A/B platforms., • Background in enterprise security and compliance (SOC 2, GDPR), • Bias to action: short specs, small PRs, daily deploys., • In-person collaboration: we’re building the NYC hub together; whiteboards > long threads. Upon joining the Knit team in this foundational role, you will receive a competitive salary, Equity Options, Healthcare (medical, dental, and vision), and Additional Coverage, a company laptop and one-time, onboarding Technology Stipend, a 401(k) with company match, flexible time-off, hybrid working, and more! Salary In accordance with New York pay transparency requirements, the expected base salary range for this role is $200,000–$275,000 annually; final compensation will be determined based on the candidate’s level, experience, and qualifications upon joining Knit. Powered by JazzHR aYoi81irtu

Job Description At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries, including financial services (particularly capital markets and fixed income), insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. Our solutions power trading desks, portfolio optimization, and risk analytics across fixed income, derivatives, and structured products. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As the Staff Machine Learning Engineer (VP) on the AI Science team, you will be responsible for architecting and deploying cutting-edge ML systems that power core business functions across the enterprise. Reporting to the Executive Director of AI Science, you will play a critical role in driving the development of scalable ML infrastructure, production-grade models, and reusable frameworks that deliver measurable business outcomes—ranging from cost optimization to top-line growth. You will bridge quantitative research and technology, with deep understanding of fixed income markets and derivatives. You will act as a technical thought leader and strategic partner in shaping the direction of the organization’s machine learning investments, fostering a culture of rigorous experimentation, reproducibility, and responsible AI. Key Responsibilities: • Design and deploy ML systems that solve high-impact business problems for critical workflows., • Develop and implement advanced ML methods including time series forecasting, reinforcement learning, optimization algorithms, and probabilistic modeling., • Lead the adoption of emerging ML techniques and tools (e.g., generative AI, LLM fine-tuning, vector databases, RAG) through rapid prototyping., • Partner with AI researchers and data scientists to translate experimental models into production-ready systems, supporting scaling and generalizability across business domains., • Own the development of foundational models and platform capabilities that serve as building blocks for downstream AI applications across the organization., • Ensure ML models are designed with safety, fairness, and transparency in mind, and aligned with internal governance frameworks and external regulatory standards., • Collaborate with cross-functional leaders in engineering, product, and business teams to embed ML-driven decision-making into core processes and workflows., • Continuously evaluate emerging ML techniques and tools, and champion their adoption through rigorous prototyping, benchmarking, and knowledge sharing., • Define and manage metrics to evaluate model performance and business impact, ensuring ML projects meet both scientific and operational standards., • Design ML-driven pricing models for fixed income securities, derivatives, and structured products., • 8+ years of experience building and deploying machine learning systems in production environments, preferably in investment banking, fixed income trading, or hedge funds, ideally within enterprise or platform-scale settings., • Proven track record of leading ML projects from ideation to production, including cross-functional collaboration and technical ownership., • Deep expertise in supervised, unsupervised, reinforcement learning or statistical modeling., • Experience with multimodal, generative AI, or large language models (e.g., LLMs, diffusion models) is a strong plus., • Proficiency in Python, along with modern ML and data stack tools (e.g., TensorFlow, PyTorch, scikit-learn, JAX, Ray, MLflow)., • Hands-on experience with MLOps principles and frameworks (e.g., CI/CD pipelines for ML, model monitoring, reproducibility)., • Strong understanding of cloud-based ML infrastructure (e.g., AWS SageMaker, GCP Vertex AI, or similar)., • Exceptional communication and collaboration skills, with the ability to translate technical details into strategic decisions., • Strong foundation in fixed income analytics, derivatives pricing, and risk management., • Commitment to responsible AI, including model fairness, transparency, and compliance with regulatory standards., • Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related discipline preferred. Preferred, but not required: • Hands-on experience with Palantir platforms (e.g., Foundry, AIP, Ontology) - including developing, deploying, and integrating machine learning solutions within Palantir’s data and AI ecosystem. Position Location This is a hybrid position based out of our New York, NY office. Compensation The base pay for this position is $290,000-300,000. A bonus will be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job Description At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As a Senior Associate, Data Scientist, you'll work alongside experienced data scientists and ML engineers to design, develop, and apply data-driven models and analyses that deliver measurable business value. Reporting to the Executive Director of AI Science, you'll gain hands-on experience working on impactful projects across the enterprise, applying advanced analytics and machine learning to areas such as financial services, insurance, and operations optimization. This is a high-growth opportunity for someone with early industry experience (or strong academic grounding) in data science and applied statistics, eager to deepen their expertise and grow within a dynamic AI team working at the frontier of applied analytics and machine learning. Key Responsibilities: • Contribute to the development of predictive and statistical models addressing business-critical challenges across diverse domains., • Conduct exploratory data analysis, feature engineering, and hypothesis testing to uncover patterns and support model development., • Collaborate with senior data scientists and ML engineers to refine models, improve accuracy, and enhance interpretability., • Support the design and evaluation of experiments and A/B tests, ensuring rigorous measurement of impact., • Clean, transform, and prepare data from diverse sources, ensuring high-quality datasets for analysis., • Build dashboards, reports, and visualizations that communicate insights clearly to technical and non-technical stakeholders., • Stay current with emerging data science methods and tools (e.g., generative AI, LLMs, causal inference) and apply them through prototyping. Qualifications: • 5+ years of experience applying data science or advanced analytics in a professional setting., • Solid understanding of statistical modeling, machine learning fundamentals, and experimental design., • Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting., • Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow)., • Strong experience with SQL and data manipulation across large datasets., • Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI). Exposure to modern collaborative data platforms (e.g., Databricks, Snowflake, Palantir Foundry) is a plus., • Excellent problem-solving skills, eagerness to learn, and ability to work in fast-paced, evolving environments., • Strong written and verbal communication skills, with the ability to translate technical findings into business recommendations., • Hands-on experience with Palantir platforms (Foundry, AIP, Ontology), including developing analytical workflows and deploying insights within enterprise environments., • PhD in Data Science, Statistics, Computer Science, or a related quantitative field. Publications in top data science / ML conferences or journals (e.g., NeurIPS, ICML, KDD, ACL, or similar)., • Open-source contributions to the data science or ML community (libraries, notebooks, packages, or tutorials). Experience presenting research or applied work at meetups, workshops, or industry conferences., • Familiarity with vector databases (FAISS, Pinecone, Milvus, Weaviate) and LLM application frameworks., • Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services., • Drive AI transformation for some of the most sophisticated financial entities., • Competitive compensation, benefits, future equity options, and leadership opportunities. Position Location This is an onsite position based in Manhattan in New York City. Compensation The base salary for this position is $190,000-$200,000 USD. A discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job DescriptionAbout Fusemachines Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. 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. Role Overview As an Applied AI Engineer(Automation), you will deliver high-impact AI and automation solutions for clients—owning work from requirements discovery through prototype and production deployment. You’ll build reliable, maintainable systems that integrate LLMs into real business workflows via APIs, automation platforms, and backend services. This is a mid-to-senior individual contributor role. You’ll collaborate closely with Solutions Architects, Delivery/Engagement leads, and Product Managers to scope, build, ship, and iterate on client solutions. Key Responsibilities • Design & Deploy: Design, develop, and deploy tailored AI and automation solutions aligned to client objectives., • Build Workflows & Services: Translate business problems into production-grade AI workflows and services using Python, automation tools (n8n/Make/Zapier or similar), and LLM platforms/APIs (e.g., OpenAI, IBM watsonx.ai, Amazon Bedrock), plus retrieval systems., • Agentic Systems: Build and deploy agentic workflows using LangChain, LangGraph, and Google ADK, including tool calling and structured outputs., • Retrieval & Knowledge Systems: Implement RAG pipelines using vector databases and search technologies (e.g., Pinecone, Elasticsearch, pgvector) and graph databases when appropriate., • Prototype → Production: Ship fast prototypes, then harden them into scalable systems (testing, reliability, deployment, monitoring) independently or with a team., • Client Partnership: Participate in discovery, run technical calls/demos when needed, and communicate tradeoffs clearly to client and internal stakeholders., • Ongoing Support & Iteration: Improve deployed solutions through feature work, bug fixes, monitoring, prompt/model improvements, and additional automations., • Documentation: Produce clear technical documentation, client demos, and internal playbooks to enable reuse and scalability., • Continuous Learning: Stay current on LLM tooling and delivery best practices to improve quality and speed.Success in This Role Looks Like, • Solutions consistently meet or exceed client expectations and show measurable impact (time saved, cost reduced, improved conversion/deflection, faster cycle time)., • Clients trust you as a go-to engineering partner and expand usage of deployed AI workflows., • Deliveries are production-ready: monitored, testable, documented, and maintainable.Required Qualifications, • 3–8 years of software or AI engineering experience (mid-to-senior)., • 2–3+ years of AI Automation, Generative AI, or Agentic AI (mid-to-senior)., • Strong Python engineering skills and experience building APIs/services (e.g., FastAPI)., • Hands-on experience integrating LLMs (e.g., OpenAI APIs or equivalents), including prompt design, structured outputs, and basic evaluation practices., • Experience with at least one workflow automation platform (n8n, Make, Zapier, or similar) and building reliable integrations., • Familiarity with RAG fundamentals and retrieval systems (embeddings, vector search); exposure to vector databases and/or Elasticsearch., • Production engineering fundamentals: Docker, cloud deployment (AWS/GCP/Azure/IBM), and experience with async/queuing patterns (e.g., Celery, Redis, Kafka)., • Comfort operating in a client-facing environment: technical calls, demos, and collaborating with cross-functional stakeholders.Preferred Qualifications, • Experience with fine-tuning LLMs or other ML models; broader ML exposure is a plus (not required)., • Familiarity with observability and tracing (e.g., LangSmith, OpenTelemetry) and prompt/version lifecycle management., • Experience with graph databases / knowledge graphs., • Familiarity with data governance and AI governance concepts (PII handling, auditability, access controls, risk awareness). 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Job Description Who We Are Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our 600+ employees work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world's most premium platforms. Taking a creative science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Now 20+ years strong, Kargo has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Who We Hire Techies who want to build the future. Creatives who want to design it better. Communicators to win business. Collaborators to build it. Data pros who turn numbers into insights. Product builders who turn ideas into innovations. Anyone eager to be on a team that doesn't stop to ask what's next, because they're already building it. Salary Range: $140,000 - $180,000 Work Type: Hybrid Mission As the AI Engineer at Kargo, you will architect, build, and scale AI-powered products and automations for Kargo's commercial organization. Operating within the Data & AI team, you are the connective tissue between revenue teams and AI infrastructure — proactively identifying high-value use cases, building intelligent workflows and agentic applications, and deploying trustworthy systems across Salesforce, Snowflake, Slack, and other internal platforms. You're both hands-on and capable of owning the strategic roadmap for AI operations at Kargo. Outcomes - What Success Looks Like in 6-12 Months • At least 3 high-impact AI automations are live and actively used by commercial teams — measurably reducing manual work or improving data quality across Salesforce, Slack, or Snowflake, • A governance model is in place covering prompt engineering standards, audit trails, and a feedback loop that drives continuous iteration, • Cross-functional stakeholders trust and use the tools you've built, and Kargo's Data & AI leadership has a clear, prioritized AI Ops roadmap that you own and drive Design & Automation • Design, build, deploy, and maintain AI-powered automations and agent workflows using modern orchestration frameworks — LangGraph, n8n, OpenAI Responses/Agents tooling, MCP-compatible architectures — with integrations across Salesforce, Slack, Snowflake, Atlassian, Google Workspace, Looker, and Airtable, • Translate business pain points into modular, extensible automation flows that are observable, debuggable, and fault-tolerant; proficient in Python or JavaScript for custom connectors and scripting, • Build production-grade LLM applications — agent workflows, retrieval systems, internal copilots — using ChatGPT Enterprise and related LLM APIs for knowledge surfacing, workflow routing, decision support, and dynamic content generation, • Work cross-functionally with Sales, Client Services, Media Strategy, Marketing, Product, and Ops to discover automation opportunities, prototype quickly, document tooling, and drive self-service adoption, • Prompt libraries, embeddings-based retrieval, or vector databases (Pinecone, Weaviate) and RAG pipelines Builder's Instinct • AdAge Best Places to Work, • ThinkLA Partner of the Year, • Built In Best Places to Work, • Cynopsis 2025 Top Women in Media - Jeannine Shao Collins, • Martech Breakthrough Awards - Best Overall Adtech Company, • Digiday Media Awards Best Event, • Cynopsis Media Impact Awards-Best CTV Platform, • Martech Breakthrough Awards-CTV Innovation, • Big Picture: kargo.com, • The Latest: Instagram (@kargomobile) and LinkedIn (Kargo)

Job DescriptionAbout Us At Vector Media, we’re building the future of Mobility Marketing, where media moves with people, meets them in real life, and makes a lasting impression. In an advertising world cluttered with screens and scrolls, we deliver real-world media with real results. Our high-impact media, including fully wrapped double decker buses and custom designed experiential experiences, turn heads in cities nationwide. And with assets in 50+ markets, we bring campaigns to life across communities, cultures, and coasts. Our experiential team allows us to activate anywhere in the country. Vector Media’s wide variety from double decker buses, light rail, digital bus shelters and a wide variety of experiential assets enables brands to connect with consumers at the street-level in cities, college campuses and sporting events. We connect brands with audiences in the moments that matter most. Founded in 1998, Vector has grown from an OOH disruptor into a full-service platform built on data, creativity, and movement. We call it Marketing in Motion, which brings unique benefits of high impact and efficiency because we bring the advertising to audiences wherever they are. But what truly sets us apart is how we show up: as partners. With our clients. With our media partners. With each other. Through accountability, innovation, and shared ambition, we’re helping brands do more than reach people, we’re helping them move people. What We Value • Accountability: Taking ownership of our actions, learning from mistakes, and earning trust through responsibility., • Growth: Supporting personal and professional development, knowing that when our team members thrive, the company thrives., • Excellence: Always striving for the best possible results and never settling for “good enough”. The VP Brand Partnerships will sell the whole Vector portfolio including Vector Sports and Vector College. The account list will cover all consumer verticals but will have focus on beauty and fashion. Previous experience in these verticals, plus experience in experiential sales is desired. The VP, Brand Partnerships will have an expertise in strategic selling, establish and cultivate relationships through proactive outreach (via phone calls, emails, in person meetings) with prospective customers such as CMO’s, SVP/VP’s Marketing, Brand Managers, Media Directors and Head of Experiential/Events. They will leverage Vector Media’s unique asset offerings and delivery methodologies positioning Vector Media as a media partner of choice within the nationwide markets we serve. This position will monetize all of the Vector portfolio including our fleet of fully wrapped Double Decker buses, public transit and Experiential Assets to brands direct. The VP, Brand Partnerships will also partner with Vector’s National agency team to build comprehensive account plans and collaborate transparently as business potentially moves from client interest to activation with their agency partners. This is a hybrid role based in New York, NY, with 3 days a week in office. Total Compensation Package Range Details: $275,000 - $350,000 including salary ($120,000-$155,000), earned commissions and potential for bonus. The salary and total compensation range is subject to change and may be amended in the future. Experience, education, skills, and other factors are considered when determining the salary and level of position offered. Who You Are: • A quick learner, self-motivated with a strong sense of professionalism, good organizational skills, ability to prioritize, multi-task and meet tight deadlines., • A thorough worker focused on attention to detail., • An entrepreneurial spirit that's motivated to drive business growth., • Bachelor’s degree., • 7-10+ years of media sales experience., • 5-7+ years of experience selling to brand-direct clients (not agencies)., • Strong book of direct clients across full spectrum of industry verticals, • Deep relationships with clients at CMO, Media Director, Brand Manager level, • Proven sales track record activating and retaining new brands (has strong brand-direct clients and can make immediate impact)., • Polished sales, presentation, and communication skills., • Exceptional team player, interested in working as part of a highly coordinated, focused organization., • Attention to delivering the highest level of sales and operational customer service., • Experience in fashion and beauty verticals, • Proactively identify new revenue opportunities; drive account growth and profitability acceleration including new business, up-sell and cross-sell opportunities., • Own extensive client communication, strategic planning and troubleshooting account complications to promote client satisfaction; develop and improve executive level relationships within named account(s)., • Provide thought leadership and consultation on aligning client business needs to products, solutions and services offered., • Drive contract negotiations for business in support of new sales, account growth and contract renewals. 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Job Description Who we’re looking for… Role: Staff Full Stack Engineer Team: Engineering Reports To: Head of Engineering Location: Knit’s NYC office (Hybrid) Operating hours: Monday - Friday 9am - 5pm EST. Travel: This role will occasionally be expected to travel for in-person internal working sessions, and our once per year US All Team Summit. [To be less than 15%] A little about us… Knit is building the agentic AI platform that helps enterprise brands run end‑to‑end consumer research. We orchestrate specialized AI agents for surveys, data collection, analysis, and reporting, delivering decision-grade insights to Fortune 1000 brands in hours, not weeks. In under two years, we’ve partnered with 50+ leading enterprise brands, including Amazon, Mars, NASCAR, JBL, ESPN, and Paramount. Knit has grown 500% in the last 12 months and raised $30.6M to date, including a $16.1M Series A in July 2025. Here are example case studies that demonstrate the value of our platform. A product demo can be found here. Overview We’re building our foundational NYC engineering team from scratch and looking for exceptional builders who are resourceful, deeply technical, and thrive in high-ownership environments. As one of the first in-house engineers, you’ll shape the core of our platform and the culture of a team that will scale to 20+ over the next 18 months. You’ll build and orchestrate AI agents, pioneer new UX paradigms, and tackle some of the hardest problems in applied AI with autonomy and end-to-end ownership. Business Impact | What you will own… • Own 0→1 and 1→N features across the stack, from design docs to building high-throughput data pipelines and scalable FastAPI services., • Architect and own the core agent orchestration engine, designing complex, multi‑agent LLM workflows (routing, tool‑use, memory, evaluation) with deterministic fallbacks, guardrails, and auditable actions required by enterprise users., • Build AI‑native, human‑in‑the‑loop UIs. Craft React/Next.js interfaces that let users collaborate safely with agents, with transparency and explainability by design., • Develop the "factory for the factory". Build our experimentation platform: CI/CD for prompts and agents, offline/online evals, drift detection, safety layers, and rollout controls., • Ship fast, safely. You’ll instrument everything for reliability, write concise design docs, add robust tests, and build dashboards and alerts for features you launch., • Partner cross‑functionally with Product, AI, Design, CS; talk to customers and SMEs, and turn ambiguous problems into shipped product., • Obsess over performance, optimizing for latency across the system: caching, model selection, distillation, batching, vector search, and infrastructure efficiency (GPU/CPU)., • Operate what you build. This includes on‑call ownership, leading incident response, and driving learning through blameless postmortems., • Level-up the team around you. Mentor and collaborate with other engineers to help make the entire team better.Our Stack, • Frontend: React, Next.js, • Backend: Python, FastAPI, • Data/ML: MongoDB, S3, Redis; Pinecone, • Infra: AWS, Docker, Kubernetes; CI/CD with GitHub Actions., • Messaging: SQS; event‑driven pipelines.This role is for you if..., • You’re a 0 → 1 builder who thrives in ambiguity and has shipped products from scratch at a startup or in a hyper-growth phase. You've seen both - early-stage hustle and later-stage scale and know how to build for it., • You’re a systems thinker with deep technical chops: you design clear architectures and write clean, tested Python and TypeScript., • You think like an owner: you spot problems, propose solutions, and build them without waiting for perfect specs. Your impact is measured in business outcomes., • You use AI as leverage. Tools like Cursor, Copilot, or Claude Code are integral to your workflow, helping you ship faster while maintaining a high standard for correctness., • You believe speed and quality aren’t opposites and can articulate the tradeoffs you make., • You communicate crisply. You share your ideas effectively and thrive in tight feedback loops with product, design, and customers., • You’ve got grit: hard problems energize you, context switching doesn’t scare you, and you’re comfortable deleting code.This role is NOT for you if..., • You see a hard line between "frontend," "backend," and "product.", • You are uncomfortable with ambiguity, rapid context-switching, and dynamic priorities., • Experience with LLM/agent systems, evals, and prompt tooling; RAG, embeddings, vector dbs., • Deep knowledge of event‑driven systems, streaming, and workflow engines., • Expertise in observability (OpenTelemetry/Prometheus/Datadog), feature flagging, or A/B platforms., • Background in enterprise security and compliance (SOC 2, GDPR), • Bias to action: short specs, small PRs, daily deploys., • In-person collaboration: we’re building the NYC hub together; whiteboards > long threads. Salary In accordance with New York pay transparency requirements, the expected base salary range for this role is $250,000–$300,000 annually; final compensation will be determined based on the candidate’s level, experience, and qualifications upon joining Knit. Powered by JazzHR tOD0xHdU6r

Job Description Applecart is the leading technology company that C-suites rely on to reach business-critical decision makers. The most important decisions are made by the hardest people to reach and influence. Historically, C-suite leaders have lacked the tools to reach the stakeholders who matter most to their business. The C-suites of hundreds of Fortune 500 companies, major agencies, trade associations, nonprofits, and governments use Applecart to put their best content in front of business-critical decision makers and those they trust — from policymakers and investors to CEOs, key employees, members of the media and more. Decision makers are informed by what they read, learn from advisors, hear from colleagues, and discuss with family and friends. To break through to them, you must reach them through the only channel that really moves them: those they know and trust. Applecart's platform uses publicly available data to map billions of social relationships between nearly every American adult and enable clients to deliver content directly to decision makers and those who matter most to them. We are hiring a Staff AI Engineer in our New York City office. About the Role: The role is for the Identity team at Applecart. The team builds and maintains best in class identity data products, tying multiple systems and data sources together. As a Staff AI Engineer, you will be responsible for leading the design and deployment of our next-generation AI-powered platforms. You will shape the technical destiny of our organization, moving beyond individual features to architect the agentic ecosystems that will handle our next phase of growth. This role will report to the Director of Engineering. What You'll Do: • Lead the design of end-to-end AI solutions using foundation models, multi-agent orchestration (MAS), and RAG pipelines. Ensure that today's technology choices support long-term scalability., • Identify systemic risks and infrastructure bottlenecks before they impact production and ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management., • Mentor other engineers. Provide design feedback that teaches thinking, recommends scalable abstractions, and builds a culture of technical excellence., • Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure., • Stay up to date with industry advancements in GenAI and apply modern technologies and methodologies to our systems., • You have 8+ years of professional software development experience, especially in the fields of data engineering and AI/ML, • Deep expertise in applied AI/ML techniques (Deep Learning, NLP, GNNs), technologies (Agentic AI, RAG, Prompt/Context Engineering), and fluency in Python or a similar backend language, • You have designed and implemented scalable data processing pipelines, and understand how to store and retrieve large sets of data, • You have experience implementing various data warehousing architectures, including products like Snowflake or Databricks, • You have proven records of leading AI/ML projects, ideally RAG applications, • Proven experience with agentic frameworks (LangGraph, CrewAI, AutoGen) and modern data infrastructure (Kafka, Spark, Vector Search)., • Hands-on experiences with graph data models and graph data processing (with graph data engines such as Neo4 or PuppyGraph) is a big plus., • You have hands-on experience in implementing the Lakehouse architecture., • You are familiar with identity resolution and have experience building identity resolution systems., • You have experience with backend API designing and implementation, • You have experience optimizing the end to end performance of distributed systems Compensation: Our compensation package consists of three components: (i) a base salary, (ii) annual cash bonus, and (iii) generous equity compensation. The base salary range for this role is between $200,000 - 250,000 based on the candidate's experience and skills relative to the requirements listed above. The salary range provided is exclusive of discretionary annual cash bonus and equity compensation. The salary range provided for this role is specific to candidates located in the New York City area. A few facts about us: • Applecart's platform has been used by hundreds of industry-leading clients spanning Fortune 500 companies like Blackstone and Intuit, leading nonprofit organizations like the Environmental Defense Fund, and top-tier advertising and communications agencies like Teneo, FGS, Weber Shandwick, and OMD., • Applecart is growing quickly — over the last 4 years, we've increased our revenue by 10X, grown our headcount by almost 5X, and we're cashflow positive., • Our senior leadership team includes two members of the Forbes 30 under 30 list for Marketing and Advertising, the former Head of Product at Moat, Oracle's online ad measurement platform, a former senior White House advisor, early sales and talent leaders from Google and Twitter, two of the Democratic Party's most successful pollsters and strategists, and alums of top-tier organizations like Bain & Company, Amazon and Simpson Thacher., • Applecart raised a $100M Series C from Blackstone's tech growth fund at the end of 2025. The company's other investors include Bain & Company, global sports, entertainment and marketing giant Endeavor, KKR Co-Founder Henry Kravis, entrepreneur Chris Burch, a founder of Palantir, senior engineering leaders at Twitter and Yelp, former Fortune 50 and advertising agency CEOs, and a number of well-known venture capitalists. Ari Emanuel, CEO of TKO and Executive Chairman of WME, Wayne Berman, Blackstone's Head of Global Government Affairs, and Risa Heller, CEO of HELLER, serve on our board., • Our work has been featured on Morning Joe on MSNBC, BloombergTV, and The Colbert Report, and in Axios, Semafor, BusinessWeek, the Associated Press, Forbes, the Washington Post, and Politico, among many others.

Job Description At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As the Staff Machine Learning Engineer (VP) on the ML Engineering team, you will be responsible for designing, deploying, and scaling advanced ML systems that power core business functions across the enterprise. Reporting to the Executive Director of ML Engineering, you will play a critical role in building production-grade ML infrastructure, reusable frameworks, and scalable model pipelines that deliver measurable business outcomes—ranging from cost optimization to top-line growth. You will act as a technical thought leader and strategic partner, shaping the organization's machine learning engineering practices and fostering a culture of operational excellence, reliability, and responsible AI adoption. Key Responsibilities: • Architect and deploy ML systems and platforms that solve high-impact business problems across regulated enterprise environments., • Lead the development of production-ready pipelines, including feature stores, model registries, and scalable inference services., • Champion MLOps best practices (CI/CD for ML, model versioning, monitoring, observability) to ensure models are reliable, reproducible, and cost-efficient., • Partner with Data Scientists to operationalize experimental models, enabling scalability and generalizability across diverse business domains., • Integrate emerging ML engineering techniques (e.g., LLM deployment, fine-tuning pipelines, vector databases, RAG systems) into enterprise-ready solutions., • Own the design of foundational ML platforms and frameworks that serve as building blocks for downstream AI applications., • Embed controls, governance, and auditability into ML workflows, ensuring compliance with regulatory standards and responsible AI principles., • Collaborate with Engineering, Product, and Security teams to embed ML-driven decision-making into enterprise platforms and workflows., • Define and track engineering and model performance metrics (latency, scalability, cost, accuracy) to optimize systems in production. Qualifications: • 8+ years of experience building and deploying machine learning systems in production environments at enterprise or platform scale., • Proven track record of leading ML engineering projects from architecture to deployment, including ownership of production-grade systems., • Deep expertise in ML frameworks and engineering stacks (TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow)., • Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++)., • Strong understanding of cloud ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployments (Kubernetes, Docker)., • Hands-on experience with data and model pipelines (feature stores, registries, distributed training, inference scaling)., • Knowledge of observability and monitoring stacks (Prometheus, Grafana, ELK, Datadog) for ML system performance., • Experience collaborating with cross-functional teams in regulated industries (finance, insurance, health) with compliance and governance needs., • Exceptional communication and leadership skills, with the ability to translate complex engineering challenges into clear business outcomes., • Hands-on experience with Palantir platforms (Foundry, AIP, Ontology), including developing, deploying, and integrating ML solutions in enterprise ecosystems., • Exposure to LLM and GenAI engineering (fine-tuning, vector search, distributed inference)., • Experience optimizing GPU clusters, distributed training, or HPC environments., • Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services., • Drive AI transformation for some of the most sophisticated financial entities., • Competitive compensation, benefits, future equity options, and leadership opportunities. Position Location This is an onsite position based in Manhattan in New York City. Compensation The salary for this position is $290,000-$300,0000. A discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job DescriptionCompany Description On-Site 1yr contract $10950/month About the Role We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure. You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. Job Description • Design and develop algorithms for generative models using deep learning techniques, • Design and build LLM-powered applications for internal and/or customer-facing use cases, • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems, • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration, • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate, • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability, • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies, • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices, • Build monitoring, observability, and feedback loops for model and application performance in production, • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems, • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities, • Mentor other engineers and contribute to architecture, technical direction, and engineering best practices Qualifications • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience, • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production, • Strong programming skills in Python and experience with backend/API development, • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design, • Experience in optimizing RAG pipelines using both structured and unstructured data, • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent, • Experience in generative AI techniques such as GANs, and VAEs, • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search, • Experience with cloud platforms such as AWS, GCP, or Azure, • Experience with Docker, Kubernetes, CI/CD, and production deployment practices, • Strong understanding of software architecture, scalability, reliability, and distributed systems, • Experience building evaluation, testing, and monitoring for AI systems, • Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications • Experience fine-tuning or adapting open-source LLMs, • Advanced knowledge of natural language processing for text generation tasks, • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks, • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar, • Experience building multi-agent systems or advanced orchestration workflows, • Experience with AI safety, guardrails, red-teaming, privacy, and governance, • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems, • Experience in customer-facing or enterprise SaaS products, • Experience in semiconductor/manufacturing, retail and e-commerce sectors Additional Information All your information will be kept confidential according to EEO guidelines.

Job DescriptionAbout Us At Vector Media, we’re building the future of Mobility Marketing, where media moves with people, meets them in real life, and makes a lasting impression. In an advertising world cluttered with screens and scrolls, we deliver real-world media with real results. From digital bus shelters and street-level storytelling to experiential activations, college campus and sports partnerships, we connect brands with audiences in the moments that matter most. Our high-impact media, including fully wrapped vehicles and custom-built experiential assets, turns heads in cities nationwide. And with a presence in 50+ markets, we bring campaigns to life across communities, cultures, and coasts. Founded in 1998, Vector has grown from an OOH disruptor into a full-service platform built on data, creativity, and movement. We call it Marketing in Motion, an approach that blends storytelling and strategy to drive results across every channel we touch. But what truly sets us apart is how we show up: as partners. With our clients. With our media partners. With each other. Through accountability, innovation, and shared ambition, we’re helping brands do more than reach people, we’re helping them move people. What We Value • Accountability: Taking ownership of our actions, learning from mistakes, and earning trust through responsibility., • Growth: Supporting personal and professional development, knowing that when our team members thrive, the company thrives., • Excellence: Always striving for the best possible results and never settling for “good enough”. Pay Range Details: $65,000 - $70,000 per year The salary range is subject to change and may be amended in the future. Experience, education, skills, and other factors are considered when determining the salary offered. What You Are • Data driven mindset with a motivation to continually learn and expand skill sets, • Capable of compartmentalizing and multi-tasking across multiple projects while adjusting to changing priorities, • Collaborative makeup that is still able to work independently on tasks for larger cross departmental goals, • Proactive nature to identify possible efficiencies and the know how to implement themWhat You’ll Bring, • Ability to craft persuasive, data-driven narratives that translate complex analytics into simple, compelling sales stories, • Strong written and verbal communication skills, with confidence presenting insights to both internal teams and external clients, • A design-oriented mindset for creating visually engaging charts, decks, and collateral that highlight the value of Vector’s offerings, • Strategic thinking skills to connect campaign-level insights to broader advertiser objectives, category trends, and market context, • Business empathy and client orientation — understanding advertiser priorities and tailoring insights to support sales strategies, • Proactive collaboration with sales partners, anticipating their needs and providing analytical solutions that help win and retain business, • Proficiencies in tools such as Tableau, Excel & PowerPoint, • Undergraduate degree in Business, Sales, Marketing, Communications, Statistics or equivalent in related fieldsWhat You’ll Do, • Participate in the execution and analysis of campaign effectiveness studies, crafting compelling stories for individual campaigns as well as developing broader macro-level narratives, and presenting insights to internal teams and client-facing stakeholders, • Manage fulfillment of all data and mapping requests utilizing tools such as Geopath, Neustar and Google Maps., • Coordinate with partner organizations that extend our capabilities and offerings for advertisers., • Lead information gathering of inventory audit submissions into industry wide platforms., • Train sales team members on best practices when speaking to clients about media metrics or meet directly with clients to disseminate any required information. Powered by JazzHR VJeakt4fEn

Job Description At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As a Senior Associate, Machine Learning Engineer, you'll work alongside experienced ML engineers and data scientists to design, build, and scale machine learning systems that deliver real business value. Reporting to the Executive Director of ML Engineering, you'll gain hands-on experience developing production-grade pipelines, monitoring frameworks, and scalable ML applications that support mission-critical business functions. This is a high-growth opportunity for someone with early industry experience (or strong academic grounding) in machine learning engineering, eager to deepen their expertise in production systems and MLOps while growing within a dynamic AI team operating at the frontier of applied ML. Key Responsibilities: • Contribute to the design, development, and deployment of ML models and pipelines across business-critical domains such as financial services and insurance., • Support production efforts, including model packaging, integration, CI/CD deployment, and monitoring for performance, drift, and reliability., • Collaborate with senior engineers to build internal ML engineering tools and infrastructure that improve training, testing, and observability workflows., • Partner with Data Scientists to operationalize prototype models, ensuring they are scalable, robust, and cost-efficient in production., • Work with large-scale datasets to enable feature engineering, transformation, and quality assurance within ML pipelines., • Implement monitoring dashboards, alerts, and diagnostics for model health and system performance. Qualifications: • 5+ years of experience building and deploying machine learning models in production environments, with exposure to monitoring and diagnostics., • Solid understanding of machine learning engineering fundamentals (pipelines, deployment, monitoring) and familiarity with data science workflows., • Experience with MLOps tools such as MLflow, Weights & Biases, or equivalent. Exposure to observability/monitoring systems (Prometheus, Grafana, ELK, Datadog) is a plus., • Proficiency in Python and familiarity with ML libraries (scikit-learn, XGBoost, TensorFlow, PyTorch)., • Strong experience with data manipulation and pipelines using Pandas, NumPy, and SQL., • Knowledge of containerized deployments (Docker, Kubernetes) and cloud ML services (AWS SageMaker, GCP Vertex AI, or Azure ML) preferred., • Excellent problem-solving skills, eagerness to learn, and ability to thrive in a fast-paced, evolving environment., • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field., • Hands-on experience with Palantir platforms (Foundry, AIP, Ontology), including deploying and integrating ML solutions in enterprise ecosystems., • Familiarity with vector databases (FAISS, Pinecone, Milvus, Weaviate) and LLM engineering workflows., • Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services., • Drive AI transformation for some of the most sophisticated financial entities., • Competitive compensation, benefits, future equity options, and leadership opportunities. Position Location This is an on-site position based in Manhattan in New York City. Compensation The base salary for this position is $190,000-$200,000. A discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job Description Position: AI/MLEngineer Location: NYCNY/Atlanta GA (In-Person Interview) Duration: 12 Months Need Only Locals to NY and GA Face to Face Interview - W2 Contract only Skills and Responsibilities: Build end-to-end AI/ML systems,including scalable ML pipelines, production-grade models, and full MLOpsinfrastructure for training, deployment, monitoring, andautomation. Develop solutions using Python,Docker, Kubernetes, Bash, PowerShell, SQL/NoSQL/vector databases, and cloudplatforms such as AWS, Azure, GCP, or OCI. Skilled in Apache Kafkafor event-driven systems Design and deploy ML models across domains like NLP/LLMs (BERT, GPT,RAG, fine-tuning), time-series forecasting, recommendersystems, and distributed training on multi-GPU or multi-nodesetups. Use MLOps and workflow tools including MLflow,Weights & Biases, Kubeflow, Airflow, and cloud AI services(Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, OCI AI). Build internal tools, CLI-first utilities, and efficient MLworkflows for high-scale production environments. Optional experience includes CI/CD (Azure DevOps, GitHubActions, Jenkins), computer vision (PyTorch/TensorFlow), Go/Rust,feature stores, model optimization, edge deployment, A/B testing, open-source ML,and real-time streaming (Kafka, Kinesis).

Job Description Job Title: Machine Learning Engineer (Level II) Location: Remote Start Date: ASAP Foam, part of Whalar Group, is the operating system for managing digital talent. Foam is a suite of intuitive pitching tools and AI-enhanced features powered by real-time, certified metrics from Instagram, TikTok, YouTube, and Snap. Foam empowers managers with the data they need to analyze content performance, inform talent negotiations, and maximize brand opportunities. With over 40,000 Creators and hundreds of millions of integrated data points, Foam streamlines the entire pitching process, eliminating spreadsheets, screenshots, and slides, allowing managers to focus on providing strategic support to their talent. Learn more at foam.io. About the role: We're looking for a Machine Learning Engineer (Level 2) to join our growing ML Engineering team and lead the development of advanced AI systems that power our platform. You'll design and deploy the core intelligence behind our products, with a focus on building autonomous, stateful AI agents capable of reasoning, learning, and acting in dynamic environments. In this role, you'll bridge the gap between research and production, architecting, training, and scaling systems that turn cutting-edge ideas into reliable, production-ready tools. You'll collaborate with engineering, data, and product teams to create cohesive, high-performance ML ecosystems across multimodal search, forecasting, and video understanding. If you're passionate about pushing the boundaries of applied AI, designing intelligent systems that think and evolve, this is an opportunity to have real impact. Here's what you'll do day-to-day: • Design and deploy autonomous AI agents, including reasoning loops, memory layers, and orchestration pipelines., • Build observability and evaluation systems to monitor reasoning, token usage, and model performance, ensuring reliable production behavior., • Lead the development of multimodal ML pipelines for semantic search, RAG, recommendation systems, and vector search across text, image, and video data., • Engineer high-throughput time-series analytics and forecasting models that connect batch OLAP queries with real-time inference., • Develop and maintain scalable asynchronous APIs and containerized services, ensuring reliability, monitoring, and performance optimization., • Partner with product and engineering teams to translate business goals into measurable ML outcomes., • Drive research-to-production pipelines for experimental AI projects and evaluate emerging technologies to advance our platform.Here's what we're looking for:, • 2+ years of experience in machine learning engineering, building production-grade ML systems., • Hands-on experience with agentic AI frameworks (e.g., LangGraph, LlamaIndex, Zep, Mem0, Langfuse, LangSmith)., • Experience building RAG pipelines, recommendation systems, and/or vector search applications (e.g., Pinecone, Vespa, PostgreSQL + pgvector)., • Strong background in time-series modeling, anomaly detection, and large-scale data analysis (e.g., Clickhouse)., • Skilled in asynchronous API design, containerization, and modern CI/CD workflows (FastAPI, Docker, Kubernetes, GitHub/Bitbucket)., • Excellent EDA skills with the ability to translate data insights into production-ready ML solutions., • Comfortable working with LLM ambiguity, designing systems that fail gracefully and learn continuously., • Proactive, independent, and curious—able to own complex features end-to-end and raise the technical bar for the team., • Strong communication skills—able to explain trade-offs between AI approaches and align technical metrics to business goals., • Medical, Dental, Vision, • 25 days of PTO + Sick days + Winter break, • Retirement planning with employer match, • Monthly phone/internet reimbursement, • Professional development stipend, • New joiner Home office allowance, • Up to 16 weeks of paid parental leave, • Volunteer days, • Identity theft protection & Legal assistance, • Company Paid Life & Disability Insurance, • Extra Voluntary Life Insurance Policy, • Voluntary Hospital and Critical Illness Insurance, • Voluntary Pet insurance

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Staff AI Engineer, where you’ll lay the cornerstone of our agent-powered future by focusing on Operational AI Systems. You will architect the foundational workflows, guardrails, and tooling that turn AI agents into everyday teammates for our internal support and operations teams. Think of it as building the AI Agent Operating System for critical internal operations: establishing the orchestration layer, standardizing tool schemas, automating the agent lifecycle, instrumenting real-time monitoring, and ensuring every solution is robust, scalable, efficient, and responsible. You’ll collaborate closely with operational specialists and engineers, meet non-technical stakeholders where they are, and deliver value in tight, incremental loops tied directly to solving their biggest problems. Because we’re still early in our agent journey, you’ll enjoy a broad scope with an expectation of mentoring peers, shaping best practices, and defining the north star for AI-native operations at Hinge. If you’re energized by building green-field systems that leverage AI to solve challenging problems, this is your invitation to help write the next chapter of how Hinge deploys AI to create a safer and more meaningful user experience on their journey to find an intimate connection.Responsibilities • Own the technical roadmap for AI automation across high-volume operational workflows, driving discovery and prioritization of high-impact AI automation opportunities while providing hands-on technical leadership from concept to production., • Prototype agentic solutions using the latest platforms and frameworks and integrate them with existing internal and third-party tools and systems., • Deliver reliable, scalable, and robust automations with the appropriate evaluations, guardrails, human oversight, and clear performance monitoring., • Drive adoption by producing documentation, running hands-on training and enablement sessions for non-technical operators, and curating prompt libraries and playbooks that empower self-service iteration., • Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to improving operational efficiency., • Embed safety, privacy, auditability, and responsible-AI standards into every workflow in partnership with Legal and Security teams., • Mentor and educate ML Engineers and Platform Engineers on new trends and research in AI/ML that can be applied to initiatives to improve user outcomes, promote safety, and improve AI-powered products and workflows.What We're Looking For, • Production-grade agent orchestration and state management: Proven ability to design, build, and operate highly reliable multi-step LLM agents, emphasizing state machine design, reliable tool calling, and recovery from failure states within coordination frameworks., • Applied AI engineering & prompt craft: Deep Python skills plus hands-on experience integrating foundation models and crafting robust prompts and utilizing vector databases., • Rapid prototyping & experimentation: Proven ability to ship and iterate quickly. Skilled at leveraging fast proofs of concept and early data to drive continuous tuning and feature improvement with high velocity., • Backend, data-systems & tool integration: Skilled at wiring external services and internal data into agent workflows through well-designed APIs and schemas., • Human-in-the-loop system design: Able to blend automation with human oversight through clear escalation paths, review checkpoints, and moderator tooling., • Operator enablement & training: Talent for translating technical workflows into clear, actionable training for non-technical teams and supporting their day-to-day adoption., • 7+ years of software or machine-learning engineering experience, with a recent focus on AI-driven automation or agentic systems., • 2+ years delivering solutions that combine automated decision support with human-in-the-loop review., • 2+ years designing and tracking operational metrics that demonstrate ROI, accuracy, and user-experience improvements for automated workflows., • 1+ years of hands-on experience designing and operating stateful, multi-step agentic workflows (e.g., LangGraph, AutoGen, or similar internal frameworks) in production, moving beyond simple single-turn chatbot or RAG demos. #Hinge We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Data Scientist NYC, NY or Remote Type: Contract About the Role We are seeking an experienced Data Scientist to join our AI Data Science team, with a strong emphasis on modern data engineering and platform-based development. This role focuses on building scalable, production-grade data and machine learning pipelines that power analytics, predictive models, and AI-driven insights across the firm, including work within our Databricks environment. Required Qualifications • § 5+ years of experience in data science, data engineering, applied machine learning, or advanced analytics roles • § Advanced proficiency in Python, with demonstrated experience building production- grade data, ML, or GenAI pipelines • § Hands-on experience working with Generative AI or LLM-based systems, including prompt design, evaluation, and application integration • § Strong grounding in data analysis, statistics, and exploratory analysis • § Experience translating business or domain questions into analytical approaches and communicating insights to non-technical stakeholders • § Strong hands-on experience with Databricks (Spark, notebooks, jobs, Delta Lake) in a production environment • § Solid understanding of data modeling, ETL/ELT patterns, and distributed data processing • § Experience deploying and maintaining machine learning models in production environments • § Excellent communication skills, with the ability to explain complex technical concepts clearly Preferred Skills • § Experience with MLflow, model registries, and experiment tracking • § Familiarity with version control and deployment workflows for data, ML, and GenAI solutions • § Experience with RAG architectures, vector databases, or semantic search • § Familiarity with GenAI evaluation techniques, including human-in-the-loop review • § Knowledge of SQL and data warehousing concepts • § Experience supporting talent analytics, people analytics, executive assessment, or professional services use cases • § Ability to design analyses and narratives appropriate for senior consultant and executive audiences • § Experience working in regulated or enterprise environments with an emphasis on reliability, governance, and trust

Job Description Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. As a Senior Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results. Key Responsibilities • Serve as a resource for creating AI agents and RAG databases to solve problems. Develop AI Agent tools to automate the retrieval, wrangling, and analysis of data., • Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to prepare datasets, conduct analytics, and develop deployable solutions with guidance from more senior resources., • Able to analyze and prepare complex and new data sources and incorporate them into analytical solutions., • Collaborate with customers and key stakeholders on initiating ideas, performing design, analysis, and process improvement., • Develop and deploy AI and ML solutions on Google Cloud Platform., • Utilize massive data sources to craft business insights and features for innovative solutions., • 7+ years of overall experience, 4+ years working as a GenAI Data Scientist., • Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git, • Machine learning and deep learning fundamentals, natural language processing (NLP), cloud computing, multi-agent systems understanding, data analysis, programming proficiency, and a grasp of ethical considerations in AI development., • Experience with agents frameworks (preferably Langchain)., • Experience with Prompt engineering- Chatbots and virtual assistants, Image generation etc., • Experience with proprietary and/or open source LLMs., • Experience in prompt engineering. This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Job DescriptionVaro is an entirely new kind of bank. All digital, mission-driven, FDIC insured and designed for the way our customers live their lives. A bank for all of us. About the role Join Varo Bank as a Principal AI/ML Architect and help us redefine the future of digital banking. This is a "builder-leader" role designed for someone who thrives in a fast-paced, high-growth environment. You won't just draw diagrams; you will engineer the intelligent systems that power our lending infrastructure. We are looking for a "technical hybrid" who thrives on autonomy and innovation. You will act as a key thought leader, partnering with the Senior Director of Data and AI/ML Engineering to drive Varo toward becoming an AI-first organization. Whether you are designing our future-state Feature Store using Databricks or deploying GenAI "summary bots" for our call centers, your work will directly influence the financial lives of millions of users. Reporting directly to the Head of Data Engineering and Analytics, you will serve as the technical North Star for our AI evolution. You will leverage the full AWS GenAI stack—from Bedrock and AgentCore to complex RAG architectures—to turn Varo into a GenAI-native powerhouse. If you enjoy moving at start-up speed with the resources of a licensed bank, this is your seat. What you'll be doing • Architecting GenAI Ecosystems: Design and implement production-grade GenAI agents using AWS Bedrock, AgentCore, and Strands Agents. Build robust RAG (Retrieval-Augmented Generation) pipelines utilizing OpenSearch and S3 Vector stores., • Scale Modern MLOps & Feature Stores: Lead the development and integration of a world-class MLOp s platform. Build and maintain Varo's Feature Store Platform architecture and ensure low-latency data availability for both real-time lending decisions and batch model training., • Data Fabric & Integration: Oversee the integration of core AWS analytics services (Glue, Glue Data Catalog, Athena) to ensure AI models have high-quality, governed data "fuel.", • High-Velocity Execution: Navigate the complexities of a fast-changing environment, collaborating across Data Science, Credit, and Product teams to move from PoC to production in weeks, not months., • Executive Influencing: Act as a key contributor to the Architecture Guild, using strong presentation skills to translate complex EKS/EC2 infrastructure and AI scaling strategies for executive stakeholders., • Drive Strategy: Serve as a subject matter expert within the Architecture Guild, presenting technical proposals and influencing senior leadership on emerging AI trends., • Collaborate Horizontally: Partner across domains including Data Science, Credit Policy, and Data Engineering to ensure technical alignment with business goals.You'll bring the following required skills and experiences, • Deep Experience: Ideally 10+ years in technical architecture with at least 5–7 years specifically focused on Machine Learning., • Architectural Foundation: Strong mastery of foundational architecture, with proven experience building agents, context stores, and vector stores., • AWS Mastery: Deep, hands-on experience with AWS SageMaker AI, Bedrock, S3, and OpenSearch. Familiarity with AgentCore and Strands Agents for autonomous task execution., • Infrastructure & Compute: Proficiency in managing server infrastructure for AI workloads, specifically Amazon EKS (Kubernetes) and EC2 optimization for model hosting., • Data Engineering Foundation: Expert knowledge of the AWS data stack: AWS Glue for ETL, Glue Data Catalog for metadata management, and Athena for serverless querying., • Certifications: AWS Certified Solutions Architect – Professional or AWS Certified Machine Learning – Specialty is highly preferred

Job DescriptionAbout zaimler AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're a small, senior team at the seed stage, deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of AI runs on, we'd love to talk. About the Job We’re looking for a Forward-Deployed Engineer to join our founding team and bring our AI-native data infrastructure to life in real-world environments. This is a hybrid role blending infrastructure, product, and delivery—you’ll work across systems, tools, and teams to bring new deployments from concept to scale. Think of it as a "jack-of-all-systems" role: one foot in Kubernetes and Ray clusters, the other in semantic pipelines and user-facing use cases. You’ll be a first responder, architect, and operator—deploying zaimler’s semantic infrastructure into dynamic enterprise settings, collaborating closely with ML and infra engineers, and making sure customers get value from day one. This role prefers candidates in or aligned to the Eastern Time Zone (EST) & will require travel onsite to customer locations. What You Will Be Doing • Build, deploy, and scale zaimler’s platform in diverse customer environments (Kubernetes-native, often hybrid cloud), • Own the infrastructure stack: provisioning, scaling, monitoring, and incident handling for data/ML pipelines., • Stand up and optimize distributed compute systems using Ray, Kubernetes, and supporting cloud services., • Bridge ML and infra—help ML engineers productionize knowledge extraction, entity linking, and retrieval pipelines, • Write Terraform, Helm charts, Dockerfiles, and bash scripts that others rely on, • Contribute to internal tooling, automation, and observability to make zaimler repeatable and scalable., • Interface directly with early customers to understand their environment, workflows, and edge cases.Prior Experience, • 3+ years of experience in backend or infrastructure roles (infra/platform, SRE, or devops welcome), • Deep familiarity with Kubernetes, Docker, Terraform, and Helm, • Experience managing or deploying distributed compute frameworks (Ray, Dask, Spark, etc.), • Fluency in at least one scripting language (Python, Bash, Go preferred), • Strong debugging skills across the stack—from network hiccups to memory leaks, • Experience deploying in cloud-native environments (AWS/GCP/Azure), • Comfortable being customer-facing and managing ambiguity in real-time, • Strong sense of ownership and bias toward action in early-stage environmentsNice to Haves, • Experience deploying or integrating LLMs or vector databases, • Background in ML Ops or building/operating data infrastructure at scale, • Familiarity with GPU optimization, multi-tenancy, or air-gapped environments, • Prior startup or zero-to-one deployment experience, • Familiar with Ray Serve, VLLM, or similar frameworks

Job Description About Syllo Syllo is on a mission to transform litigation. Our product is an AI-powered litigation workspace that enables lawyers and paralegals to safely harness the power of language models throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit. We are a mission-driven venture and recognize the enormous societal benefits that will result from a legal system that works better for everyone. We are seeking a skilled and fast-moving Senior AI Engineer to join our team. This role is focused on the practical application of AI, specifically leveraging Large Language Models (LLMs), to build robust, scalable, and impactful user-facing features. This is an engineering-centric role—you will be an expert at building and integrating production systems, not primarily a research scientist. The Responsibilities • System Design & Implementation: Design and build high-performance, production-level AI-powered features and services, with a focus on reliability and scalability., • Develop robust engineering solutions to mitigate the inherent unreliability of LLMs. This includes implementing effective guardrails, validation pipelines, error handling, caching, and failover/fallback mechanisms to ensure a high-quality user experience even when the model misbehaves., • Focus on optimizing latency, throughput, and cost efficiency for all AI-powered services., • Serve as an engineering expert in integrating models and data feeds with existing business logic and APIs., • Engineering Best Practices & Quality:, • Champion and enforce high standards for code quality, architectural design, and system documentation., • Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the robustness of AI features before and after deployment., • Participate actively in peer code reviews to maintain a high bar for engineering standards across the team., • Feature Delivery & Ownership:, • Take ownership of the full lifecycle of new AI features, from initial design and prototyping to testing and deployment into the production environment., • Own the end-to-end development of new features, including API design, integration with front-end services, persistent data storage, and comprehensive monitoring/alerting., • Work closely with product managers and other engineers to scope, estimate, and deliver features on a fast iterative cycle., • Pipeline Enhancement: Quickly onboard onto our existing codebase to understand, maintain, and significantly enhance existing data and feature pipelines, improving their efficiency and robustness., • Tooling & Velocity: Embrace and utilize AI-powered developer tools (such as GitHub Copilot) to maximize your efficiency, demonstrate a commitment to continuous learning, and set a high bar for engineering velocity. Qualifications • Deep Engineering Fluency & Quality Focus: Proven ability to build and deploy complex, high-quality software systems with an emphasis on maintainable code, rigorous testing, and engineering best practices., • Python Proficiency: Fluent in Python and its ecosystem for backend services and data processing., • System Design Expertise: Strong grasp of system design principles, including distributed systems and API design., • Demonstrated ability to design scalable distributed systems, including expertise in microservices architecture., • Codebase Agility: Excellent ability to read, understand, and navigate an unfamiliar codebase quickly., • Fast Learner: A demonstrable history of rapidly acquiring new technical skills and applying them to solve business problems. Great to Have • AI/ML Feature Experience: Experience directly building, shipping, and maintaining AI-powered products, agents, or intelligent features in a commercial setting., • LLM/Generative AI Exposure: Familiarity with the unique engineering challenges of integrating Large Language Models into a production environment., • Hands-on experience with LLM operationalization challenges (MLOps for LLMs), including prompt engineering, working with vector databases, RAG systems, or managing context windows., • Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) for deploying and managing services. United States - Remote Pay Range$170,000—$220,000 USD

Job DescriptionAbout Monstro Monstro is an AI-native fintech platform reimagining how people and institutions manage money. We're building a modern foundation for financial decision-making—combining intelligence, automation, and elegant design to help users make smarter choices with confidence. Our team includes experienced builders from leading fintech, wealth management, and technology companies, united by a shared goal: to create a category-defining product that transforms how financial insight is delivered and acted on. About the Role We're looking for a Senior AI Engineer who is, first and foremost, a strong software engineer—someone who writes clean, well-tested, production-grade code and brings the same engineering rigor you'd expect from any senior engineer on our team. On top of that foundation, you'll bring deep expertise in AI systems: building agentic workflows, deploying both commercial and open-source models, and designing intelligent features that work reliably at scale. You'll build the AI-powered capabilities at the core of our platform—systems that can reason, plan, and act on behalf of users while remaining trustworthy, explainable, and aligned with user intent. Because we deploy within our partners' infrastructure, you'll work with both commercial model APIs (such as Anthropic's Claude) and self-hosted open-weight models, choosing the right tool for each use case based on performance, cost, security, and deployment constraints. What You'll Do Build Production Software Write clean, maintainable, well-tested code. Design APIs, services, and data models with the same rigor expected of any senior engineer. Participate in code reviews, contribute to architecture decisions, and uphold engineering best practices across the codebase. You'll own features end-to-end—from design through deployment and monitoring. Design and Build Agentic AI Systems Design and implement autonomous AI agents with planning, memory, and tool-use capabilities. Build orchestration layers that coordinate multi-step agent workflows, manage conversational context, and handle fallback behaviors gracefully. Integrate both commercial model APIs and self-hosted open-weight models depending on the requirements of each use case. Deploy and Operate AI Models Deploy and manage self-hosted open-weight LLMs within secure cloud environments. Optimize inference performance through quantization, batching strategies, and efficient serving frameworks (vLLM, TGI, or similar). Integrate commercial model APIs (Anthropic, OpenAI, etc.) where appropriate, managing cost, latency, and reliability. Build systems that can operate in environments with limited or no external network access. Build RAG & Knowledge Systems Design retrieval-augmented generation pipelines that ground AI responses in authoritative, up-to-date information. Develop chunking, indexing, and retrieval strategies optimized for financial content. Integrate AI systems with structured knowledge bases and real-time data sources. Ensure AI Quality and Safety Develop evaluation frameworks that measure reliability, consistency, and safety—not just accuracy. Build automated testing pipelines for AI systems, including regression testing, adversarial testing, and edge case detection. Implement guardrails that prevent harmful, biased, or off-topic outputs. Design transparency mechanisms and audit trails that support compliance and debugging. Adapt and Fine-Tune Models Adapt open-weight foundation models for domain-specific tasks using techniques like instruction tuning, LoRA, QLoRA, and parameter-efficient fine-tuning. Implement prompt engineering strategies and evaluate their effectiveness. Optimize model performance for latency, cost, and quality tradeoffs. Monitor and Improve Production AI Implement monitoring for model drift, latency, error rates, and output quality. Design for graceful degradation when models or services underperform. Create feedback loops that surface production issues and drive continuous improvement. Collaborate with Data Engineers and ML Engineers to ensure seamless integration with data pipelines and feature stores. Mentor and Collaborate Mentor junior engineers on AI development and software engineering best practices. Collaborate with product managers and domain experts to translate business needs into AI capabilities. Communicate complex AI concepts clearly to technical and non-technical stakeholders. What We're Looking For Core Engineering Experience • 7+ years of software engineering experience, with a track record of shipping production systems, • Strong proficiency in Python and/or Go, with clean, well-structured code, • Solid understanding of software engineering fundamentals: system design, API design, testing, code review, CI/CD, and version control, • Experience with containerization (Docker, Kubernetes) and cloud infrastructure, • 3+ years of hands-on experience building AI/ML-powered features or products, • Experience building agentic AI systems—chat interfaces, multi-step workflows, tool-use patterns, and orchestration frameworks (LangChain, LangGraph, or similar), • Working experience with both commercial LLM APIs (Anthropic, OpenAI) and open-weight models (LLaMA, Mistral, Qwen, or similar), • Experience designing and implementing RAG pipelines with vector databases, • Strong understanding of prompt engineering and LLM behavior optimization, • Familiarity with model serving frameworks (vLLM, TGI, Triton, or similar) and inference optimization techniques, • Experience with model adaptation techniques (LoRA, QLoRA, PEFT, instruction tuning), • A problem solver at heart—you dig into complex problems, explore options, and find practical solutions rather than waiting for direction, • Proactive and self-driven; you identify opportunities and risks before they become blockers, • Innovative and curious; you keep up with a fast-moving field and bring new ideas to the team, • Passionate about building AI systems that are both powerful and trustworthy, • Excellent communicator who can explain AI behavior and limitations clearly to any audience Why Monstro?, • Ownership & Impact: Shape the future of AI-powered finance—building a category-defining product used by consumers and institutions around the world., • Elite Team: Join a team with leadership that has a track record of scaling companies from early stage to major exits., • Principles-Driven Culture: Work in a culture that values speed, ownership, and impact—what most companies achieve in 90 days, we do in 45., • Comprehensive Compensation Package: Competitive salary, equity, and robust benefits package, including paid health, vision, dental, and disability coverage. Note: This role will be hybrid in office for those in the NYC metro or remote for those in the Denver metro area (but with the expectation of periodic travel to our NYC office) Compensation Range (New York City): $189,000 - $235,000 Compensation Range (Denver Metro): $166,000 - $207,000 *The posted range reflects the base salary for this role across the market ranges for each location. Final compensation will depend on a variety of factors, including experience, skills, internal leveling, and market conditions, and will be offered within the stated range in accordance with applicable pay transparency laws. Ready to Build With Us? If you're excited to contribute to a high-bar team building something meaningful, we love to hear from you!

Job Description Maven is the world's largest virtual clinic for women and families on a mission to make healthcare work for all of us. Maven's award-winning digital programs provide clinical, emotional, and financial support all in one platform, spanning fertility & family building, maternity & newborn care, parenting & pediatrics, and menopause & midlife. More than 2,000 employers and health plans trust Maven's end-to-end platform to improve clinical outcomes, reduce healthcare costs, and provide equity in benefits programs. Recognized for innovation and industry leadership, Maven has been named to the Time 100 Most Influential Companies, CNBC Disruptor 50, Fast Company Most Innovative Companies, and FORTUNE Best Places to Work. Founded in 2014 by CEO Kate Ryder, Maven has raised more than $425 million in funding from top healthcare and technology investors including General Catalyst, Sequoia, Dragoneer Investment Group, Oak HC/FT, StepStone Group, Icon Ventures, and Lux Capital. To learn more about Maven, visit us at mavenclinic.com. An award-winning culture working towards an important mission – Maven Clinic is a recipient of over 30 workplace and innovation awards, including: • Fortune Change the World (2024), • CNBC Disruptor 50 List (2022, 2023, 2024), • Fortune Best Workplaces for Millennials (2024), • Fortune Best Workplaces in Health Care (2024), • TIME 100 Most Influential Companies (2023), • Fast Company Most Innovative Companies (2020, 2023), • Built In Best Places to Work (2023), • Fortune Best Workplaces NY (2020, 2021, 2022, 2023, 2024), • Great Place to Work certified (2020, 2021, 2022, 2023, 2024), • Fast Company Best Workplaces for Innovators (2022), • Design, build, and deploy end-to-end AI-powered solutions using AI models (e.g., OpenAI, Gemini) and modern orchestration techniques such as RAG, multi-call prompting, and agent frameworks to power intelligent product experiences., • Work with product, data, and engineering teams to turn rich healthcare data into actionable insights and intelligent workflows that improve the care journey for both members and providers., • Develop robust ML pipelines and platform components that enable model experimentation, fine-tuning, training from scratch when needed, and deployment in production environments — with a strong focus on scalability, safety, and performance., • Collaborate cross-functionally to prototype and productionize AI-driven features such as personalization, care routing, decision support, and summarization., • Drive architecture discussions and technical decision-making across AI/ML systems, promoting best practices in coding, design, and evaluation of AI models., • Mentor engineers and data scientists across the organization, fostering a strong culture of curiosity, experimentation, and AI fluency., • A strong track record in either:, • Building AI-powered applications using foundation models and orchestration techniques (e.g., RAG, agents, LangChain, vector search), or, • Deep experience as a data scientist working across the data science lifecycle — from understanding messy, complex datasets to training or fine-tuning models that deliver measurable business impact., • Experience integrating and deploying foundation models via platforms like OpenAI, Google Vertex AI, or similar., • A clear understanding of how to work with health-related datasets, including user behavior, care journeys, health profiles, and provider interactions., • Fluency in Python and experience with backend or platform engineering in one or more additional languages (Go, Java, etc.)., • Familiarity with cloud-native systems (e.g., containerization, orchestration, distributed systems) and how to operationalize AI solutions within them., • Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows., • A collaborative mindset, strong communication skills, and a passion for using AI to improve healthcare outcomes., • Bachelor's or Master's degree in Computer Science or related field, or equivalent experience. Maven embraces a flexible hybrid work model. Our teams primarily operate from the New York Metropolitan area, NY, San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C. For those in our New York City office, we encourage in-person collaboration by requiring team members to work onsite three days a week (Tuesday, Wednesday, Thursday). For those based in San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C., we encourage in-person collaboration by requiring team members to attend quarterly Work Together Days within these cities. This policy aims to balance remote work flexibility with the benefits of face-to-face interaction. At Maven we believe that a diverse set of backgrounds and experiences enrich our teams and allow us to achieve above and beyond our goals. If you do not have experience in all of the areas detailed above, we hope that you will share your unique background with us in your application and how it can be additive to our teams. Benefits That Work For You Our benefits are designed to support your health, well-being and career development, helping you thrive both personally and professionally. We remain focused on providing a competitive benefits package for our employees. On top of standards such as employer-covered health, dental, and insurance plan options, we offer an inclusive approach to benefits: • Maven for Mavens: access to the full platform and specialists, including care for mental health, reproductive health, family planning and pediatrics., • Whole-self care through wellness partnerships, • Hybrid work, in office meals, and work together days, • 16 weeks 100% paid parental leave and new parent stipend (for Mavens who've been with us for 1 year+), • Annual professional development stipend and access to a personal career coach through Maven for Mavens Maven is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. Maven is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Maven Clinic interview requests and job offers only originate from an @mavenclinic.com email address (e.g ). Maven Clinic will never ask for sensitive information to be delivered over email or phone. If you receive a scam issue or a security issue involving Maven Clinic please notify us at: . For general and additional inquiries, please contact us at .

Job Description Senior Software Engineer (Agentic AI / Healthcare) Location: New York, NY (Manhattan), Hybrid (3 days onsite) Compensation: $150,000–$250,000 base + equity Contact / Apply: Ryan Johnston - About Our Client Our client is a venture-backed healthcare technology company based in New York and Toronto, building agentic AI solutions that reimagine how medications are prescribed, verified, and supported across the pharmacy ecosystem. Backed by $4M in funding and trusted by multiple Fortune 50 healthcare organizations, they're scaling quickly and expanding their AI product line. As an early engineering hire, you'll play a meaningful role in shaping architecture, shipping production systems, and balancing speed with quality. The work directly impacts pharmacy workflows and, most importantly, patient outcomes. Mission Our client is building a world where medication delays are impossible. From the moment a prescription is written, the path to therapy start should be clear, fast, and predictable. Their platform connects the fragmented steps that slow medication access, intake, coordination, utilization management, and clinical services, so patients start therapy sooner. The Role Our client is hiring a Senior Software Engineer to design and build autonomous, agentic systems that run complex, multi-step pharmaceutical workflows end-to-end. This is a backend-leaning role with broad scope: you'll work across orchestration, integrations, reliability/observability, and the practical realities of healthcare systems. This role is ideal for someone who enjoys ambiguous problems, can ship end-to-end, and wants to build real product in a regulated, high-stakes domain. What You'll Do * Design and build autonomous agents that handle multi-step pharmacy workflows end-to-end * Architect communication systems that coordinate across organizational boundaries (providers, payers, pharmacies, vendors) * Build orchestration layers for long-running tasks, including graceful failure handling and human-in-the-loop escalation * Develop frameworks enabling agents to interact with external pharmacy systems, databases, and APIs * Implement evaluation + observability infrastructure to monitor agent behavior in production (quality, drift, failure modes) * Integrate with healthcare data standards and legacy pharmacy systems * Scale systems for real-time processing across multiple pharmacy networks What Our Client Is Looking For Must-Have Qualifications * 5+ years of software engineering experience with a strong backend focus * Proficiency in Python or TypeScript and deep backend fundamentals (APIs, data stores, concurrency, distributed systems) * Experience with service-oriented architectures and web frameworks (FastAPI, Flask, or equivalent) * Strong API design skills (clean, versioned APIs) * Familiarity with caching, messaging, and databases (e.g., Redis, Kafka, SQL/NoSQL, vector databases) and how to apply them for performance and reliability * Cloud experience (Azure, AWS, or GCP) * Experience building and deploying agentic AI systems, including tool use, planning, memory, and orchestration patterns * Proven ability to ship ambiguous projects end-to-end with minimal guidance and own outcomes * Based in NYC and able to commute to Manhattan 3 days/week Nice-to-Haves * Experience integrating with healthcare/pharmacy systems or healthcare data standards * Experience building evaluation harnesses for agent reliability and hallucination mitigation * Prior work in regulated environments where correctness and auditability matter Compensation & Perks * Competitive compensation: $150k–$250k base + stock options * Full medical, dental, vision coverage * Unlimited PTO + 2 weeks company-wide holiday closure * Complimentary breakfast daily and weekly team lunches (in-office) * Professional development stipend Why This Role This is a rare opportunity to be early, own architecture, and build agentic systems that directly improve medication access—where execution quality matters and the impact is tangible.