Test And Evaluation Lab Tech Jobs

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

Experienced Ordnance Specialist Company: Boeing Aerospace Operations The Boeing Company has an exciting opportunity for an Experienced Ordnance Specialist to join our team located in Hertford, NC . The ideal candidate will be upbeat and ready to react when given an unexpected time sensitive task. You will be asked to work alongside the client and other agency’s providing physical support along with scheduling range set up and cleanup operations with public works. This position will require you to work on outside ranges in all weather conditions. Position Responsibilities: Provide support to instructors prior to and during range activities Cleanup all buildings and work areas on range Maintain accurate levels of demolitions, chemicals and incendiary materials on range Keep inventory on all equipment, explosive and ordnance usage Receive explosives and incendiary material shipments Coordinate all demolition range work with public works Keep ranges supplied with safety and first aid supplies Keep electrical firing systems in repair and working order Fabricate targets and related training materials for use on ranges Maintain and stock storage areas Perform other duties assigned Knowledge of range regulations and safety procedures Maintains awareness of range schedule and provides status to management of any identified issues Responds to trouble calls and resolves a variety of complex problems Is able to use a wide variety of complex test equipment Provides technical expertise in the evaluation of products or equipment and makes recommendations Has specialized knowledge in the use of all hand

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the physical constraints of real-world systems to improve people’s lives. About Role We are looking for an Operations Program Manager - Robotics Data Acquisition to own the day-to-day operating rhythm in our data collection facilities. You will work closely with operators, technicians, program managers, and engineers to keep rigs ready, campaigns moving, issues resolved, and performance improving. This is a hands-on operations role that requires you to be comfortable spending time on the floor, working through ambiguity, and using data to make the operation more reliable and efficient. This role is based in San Francisco, CA and requires in-person presence 5 days a week. In this role you will: Coordinate daily operations readiness across workstations, operators, materials. Track core operating metrics including utilization, cycle time, throughput, downtime, operator productivity, and data quality. Identify bottlenecks through workflow analysis, time studies, and capacity modeling, then drive practical fixes. Execute the rollout of new hardware, sensors, tools, and process changes with Engineering, Operations, Facilities, Supply Chain, and Safety. Identify equipment readiness issues and coordinate with technical support to keep workstations, and test equipment calibrated, configured, maintained, and ready for rollouts and evaluations. Lead root cause analysis for recurring operational issues and follow through on corrective actions. Provide operation input to create and maintain SOPs, work instructions, training materials, and process controls. Identify and flag resource constraints and manage issue escala

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We are currently seeking a Quantitative Risk Analysis Manager to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with managing a team responsible for reporting and analytics regarding Collateral offerings as well as Collateral model business user supports. The role requires deep understanding of data and current code base, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for enterprise Collateral models for user acceptance testing and provide feedback. Your Impact: Manage a team of three to four people Complete baseline processes and reports monthly and interpret results as it relates to collateral risk management Follow appropriate controls and standards established to maintain and document for processes & reports. Participate in performing ad-hoc analytics in support of collateral policy Cleanse, manipulate and analyze large datasets using statistical software Collaborate with team members and interact across organizational lines to meet business objectives Qualifications: Degree in

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight : Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful agent autonomy (for example future versions of auto-review ). About the Role This role focuses on oversight and system-level mitigations that enable increasingly capable agents to operate safely and autonomously in real environments. We prioritize building oversight systems that are used in practice today, both internally and externally (see our recent work on action monitoring for codex and former code review ). We also study longer-term questions about how increasingly capable agentis systems can be supervised, constrained, and corrected. We’re looking for a safety&security minded researcher or engineer who can reason rigorously about security boundaries and agent behavior, then build and test practical mitigations. A background in AI control or security is welcome but not required. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and evaluate system-level controls for agent actions like agent-based review. Plan how they fit in a broader syste

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI syst

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. The Role You'll be our dedicated expert in query execution and query performance. That means owning the query execution service end-to-end: working on caching strategies, incremental execution, query rewrites, and other optimizations that directly affect the speed and cost of running Observe at scale. You'll also be the go-to resource when query latency issues arise during customer evaluations and new deal cycles, diagnosing root causes

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

SmartBear delivers application integrity for modern tech stacks, ensuring continuous, measurable assurance that software just works as intended with governance to operate at AI speed and scale. SmartBear offers deep test automation, API lifecycle management, and observability capabilities. With integrations across the SDLC, it sets a new quality standard for application delivery teams. SmartBear is trusted by developers, testers, and software engineers across 32,000 organizations, including 75% of the largest financial institutions and industry leaders such as Adobe, JetBlue, and Microsoft. SmartBear’s open source tools are downloaded more than 100 million times a month and have earned over 30,000 GitHub stars from the developer community. With its best-loved brands, including Swagger, TestComplete, Reflect, QMetry, Zephyr, and more, SmartBear meets customers where they are to make our technology-driven world a better place. Learn more at www.smartbear.com , or follow us on LinkedIn , X , and Reddit . At SmartBear, you will be part of a dynamic team solving one of the most critical challenges facing modern businesses: ensuring the integrity of software in an AI-driven world. Whether you are working directly with customers, driving go to market strategies, supporting operations, building products, or enabling teams, your contributions help shape the future of software quality for organizations worldwide. Join us in our mission. Summary Support enterprise customers as they adopt BugSnag to improve application stability and software quality. Partner with Sales to deliver technical demonstrations, proof of concepts, and customer evaluations. Build expertise in observability, troubleshooting, and customer-facing solution engineering while growing your technical career. Product Introduction BugSnag helps engineering teams proactively monitor application stability by identifying, prioritizing, and resolving software errors across web,

SmartBear delivers application integrity for modern tech stacks, ensuring continuous, measurable assurance that software just works as intended with governance to operate at AI speed and scale. SmartBear offers deep test automation, API lifecycle management, and observability capabilities. With integrations across the SDLC, it sets a new quality standard for application delivery teams. SmartBear is trusted by developers, testers, and software engineers across 32,000 organizations, including 75% of the largest financial institutions and industry leaders such as Adobe, JetBlue, and Microsoft. SmartBear’s open source tools are downloaded more than 100 million times a month and have earned over 30,000 GitHub stars from the developer community. With its best-loved brands, including Swagger, TestComplete, Reflect, QMetry, Zephyr, and more, SmartBear meets customers where they are to make our technology-driven world a better place. Learn more at www.smartbear.com , or follow us on LinkedIn , X , and Reddit . At SmartBear, you will be part of a dynamic team solving one of the most critical challenges facing modern businesses: ensuring the integrity of software in an AI-driven world. Whether you are working directly with customers, driving go to market strategies, supporting operations, building products, or enabling teams, your contributions help shape the future of software quality for organizations worldwide. Join us in our mission. Summary Support enterprise customers as they adopt BugSnag to improve application stability and software quality. Partner with Sales to deliver technical demonstrations, proof of concepts, and customer evaluations. Build expertise in observability, troubleshooting, and customer-facing solution engineering while growing your technical career. Product Introduction BugSnag helps engineering teams proactively monitor application stability by identifying, prioritizing, and resolving software errors across web,

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role As AI agents become more capable at software engineering, and automate more of our internal work, they could become a dangerous cyber threat. People in this role will help OpenAI prepare for security threats from advanced AI agent insiders. In this role, you will: Identify paths by which capable future internal AI agents could compromise OpenAI. Design security controls - focusing on measures with long lead times that benefit from advanced preparation. Stress-test defenses with AI agent evaluations and penetration tests You might thrive in this role if you: Are deeply technical across security and modern infrastructure, and are comfortable digging into the details of operating systems, cloud, containers, CI/CD, or distributed systems. Have strong software engineering skills and enjoy building prototypes yourself. Are interested in engaging with stakeholders and can do so effectively. Bonus: have experience securing cloud infrastructure, and are deeply familiar with core components of the AI stack. Compensation Range: $293K - $405K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. As an Account Engineer , you’ll play a key role in delivering technical expertise and building relationships with prospects and customers as they explore the Snowflake AI Data Cloud. This is a fantastic opportunity to grow your career, develop your skills, and make an impact in a supportive and dynamic environment. You’ll work alongside experienced team members, contributing to a variety of customer engagements, from technical evaluations to inspiring future-state architectures. This role blends technical problem-solving, collaboration, and customer focus, making it an exciting step for someone looking to grow into a technical customer-facing role. What You'll Do: Support Customer Engagements: Assist in presenting Snowflake’s technology and vision to diverse audiences, from technical contributors to business leaders. Develop your skills in aligning technical solutions with business outcomes. Contribute to Technical Wins: Collaborate with customers to plan and execute technical evaluations and proof-of-concept demonstrations, supported by senior team members. Help tailor solutions to customer needs while learning how to communicate business value effectively. Learn & Build Relationships: Partner with customers and technical champions to foster trust and collaboration. Bu

About the Team The Early Access Program (EAP) team leads high-impact alpha programs at the intersection of customers, Product, Research, Engineering, GTM, Security, Legal, and launch teams. We partner with customers to test emerging capabilities with real-world use cases, surface actionable insights, and support launch decisions. Our team is made up of builders who learn quickly, collaborate deeply, create clarity in ambiguity, communicate openly, and iterate constantly. About the Role We’re hiring an Early Access Deployment Engineer to lead technical engagements with customers who are leveraging our frontier capabilities to solve real-world use cases. You will work at the earliest—and often messiest—stage of development, when capabilities are still unclear, tooling and processes are evolving, and the path from promising technology to a valuable real-world application has yet to be defined. You will be a hands-on builder, problem solver, and technical partner to customers and our research/product team. You’ll push beyond initial assumptions, identify high-value use cases, prototype solutions, design useful evaluations, and troubleshoot what is and is not working. Managing multiple customer engagements at once, you will help customers navigate ambiguity and difficult technical decisions while translating their experience into clear, actionable feedback for Research and Product. You will also own the end-to-end execution of early access programs—from onboarding customers, supporting live experimentation, synthesizing findings, and informing launch decisions. You’ll collaborate deeply with Research, Product, Engineering, Applied Evals, GTM, Legal, Security, Marketing, and other launch partners to create clarity, manage risk, and keep programs moving through changing conditions. Success in this role means turning frontier capabilities into real-world customer value and high-quality research signals. You will develop reusable technical approaches from early deployments,