Field Implementation Manager Jobs

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

Bits Code is Datadog’s cloud coding agent which fixes the problems that Datadog surfaces, as automatically as possible. You’ll shape the architecture, tools, processes, and culture that keep security risk very low while working hands-on with the team to ship product features quickly. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Own the security architecture and implementation of Bits Code from early design through production operation. Work with engineering, product, infrastructure, and security teams to identify risks and shape the product. Build threat models for new and existing agent risks such as prompt injection. Help the team ship secure software fast by writing and maintaining core libraries, and guiding processes and culture. Work with our sandbox teams on how Bits Code executes untrusted workloads. Be on call. Datadog culture is that you build it, you run it. Who You Are: You have a BS/MS/PhD in Computer Science, Engineering, or a related scientific field, or at least 5+ years of professional experience, with a background in product security, application security, or security architecture. You have experience securing systems that operate across complex trust boundaries. You have experience building and operating full stack systems at scale. You are familiar with security risks in agentic systems and have experience designing against them. You make pragmatic security trade-offs. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Skilled, knowledgeable, and kind teammates to work with a

NK Securities Research is a leading financial firm that leverages cutting edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High Frequency Trading across different asset classes. With a focus on innovation, entrepreneurship, and collaboration, we aim to foster a dynamic work environment that reflects a startup culture. Role Overview As an FPGA Developer, you will design, implement, and rigorously test RTL (Register-Transfer Level) designs to power our high-frequency trading strategies. Your contributions will play a pivotal role in reducing system latency and enhancing performance, directly impacting trading outcomes. Key Responsibilities Design and Implementation: Develop high-performance RTL designs using VHDL or Verilog for FPGA-based systems. Optimize hardware implementations for ultra-low latency and high throughput. Testing and Debugging: Perform thorough functional and timing testing of RTL designs, ensuring adherence to specifications. Debug and resolve issues using FPGA debugging tools such as SignalTap, ChipScope, or ModelSim. Collaboration and Documentation: Work closely with hardware and software teams to ensure seamless integration of FPGA solutions with the Software Trading Stack. Maintain clear and comprehensive documentation of designs, test cases, results and benchmarks Qualifications Technical Skills: RTL Development: Strong fundamentals in digital logic design, Boolean algebra, FSMs and synchronous design. Proficiency in VHDL or Verilog/SystemVerilog, with a strong focus on efficient and optimized designs. FPGA Tools: Hands-on experience with industry-standard tools such as Xilinx Vivado. Testing and Verification: Expertise in writing testbenches and conducting simulation-based verification. Familiarity with static timing analysis and achieving timing closure. Familiar with CocoTB or any similar testing setup. Debugging: Proficiency in GHDL synthesis a

We are looking for a passionate and energized engineer to accelerate the integration of APIs across the CUDA-X math library software stack into modern LLM and agentic AI workflows. Leading organizations globally are using GPU-powered data centers for AI, data analytics, and scientific simulations, driving advancements in fields like LLMs, computer vision, CAE, EDA, and autonomous vehicles. Our team develops the GPU-accelerated libraries and SDKs essential for these technologies. In this role, you will be responsible for ensuring both human engineers using LLMs and AI agents alike to build high-performance applications with ease through effective utilization of CUDA-X libraries. Do you have the rare blend of technical, developer experience and communication skills? If so, we would love to learn more about you! What You'll Be Doing: Drive the architecture and implementation of math libraries APIs and documentation structures designed to be LLM-first: introspectable, explainable, and easily synthesized by AI agents. Work with internal and external stakeholders to deliver timely LLM-enhanced library releases. Build metrics, tools and processes to measure impact and quality of LLM/agentic code generation. Prototype tooling and solutions to help transform math libraries’ APIs into LLM-friendly representations across popular codegen tools. What We Need To See: PhD or MSc’s degree in Computational Science, Computer Science, Applied Math, or related science or engineering field of study is preferred (or equivalent experience) 3+ years of experience Robust knowledge of LLMs, finetuning, RL, building RAGs, MCP, and building agenting tooling Proven experience designing clear, composable APIs and writing high-quality, well-documented code for complex technical domains Ability

Job ID: 111266 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Responsibilities: Design and conduct studies across key product areas, utilizing methods such as ethnographic/field research, surveys, concept testing, usability testing, and any other methods you find impactful. Partner with our data scientists to provide qualitative context for their quantitative insights. Review, analyze, and communicate mixed methods data to generate tactical and strategic insights, as well as actionable recommendations that drive product innovation and design improvements for users. Find creative and compelling ways to generate, present, and evangelize results and recommendations throughout the company, in order to help cultivate a highly informed, more effective, and more empathetic organization. Work with cross-functional partners to shape product direction based on research findings and follow-up with partners about implementation to understand how findings are being used. Experience: Education and Experience: Master's degree or foreign equivalent in psychology, data analysis, statistics, or related field. 1 year of experience in job offered, data analysis, or related occupation. Skills: Experience with research and statistical analysis. Experience conducting qualitative and quantitative research. Experience analyzing data surveys, experimental studies, content analysis, and correlational research. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligib

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the top AI-native startups building in the physical world, across robotics, semiconductors, aerospace, manufacturing, and civil infrastructure, as they grow from early product to scale. Some of these companies build the hardware itself and want Claude woven into how they design, test, and operate it, and others build the software that engineers everywhere use to design, simulate, test, and scale, and this role works with both. You'll lead deep technical engagements, partnering directly with startup software and hardware engineering teams to help them build their products on Claude and run their own engineering with it, advising on implementation and agent design as they build what is newly possible with AI in the physical world. You will bridge the gap between what Claude can do and what it takes to build real things, working alongside some of the strongest teams in the field on problems that matter and helping mechanical, electrical, and process engineers get the kind of step change that software engineering has had from agentic coding with tools like Claude Code. Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your engineering domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable physical AI startups to succeed with Claude. Responsibilities Se

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the top AI-native life sciences and biotech startups as they grow from early product to scale. Some of these companies build products on Claude that they sell to the rest of the industry, and others do the science themselves and want Claude woven into how their own research runs, and this role works with both. You'll lead deep technical engagements, partnering directly with startup engineering and scientific teams to help them build their products on Claude and run their own research with it, advising on implementation and agent design as they build what is newly possible with AI in the life sciences. You will bridge the gap between what Claude can do and what the life sciences need, working alongside some of the strongest teams in the field on problems that matter and pushing the boundaries of AI in science as you go. Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your scientific domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable life sciences startups to succeed with Claude. Responsibilities Serve as a deep technical advisor to high-potential life sciences and biotech startups, whether Claude sits inside the product they sell or inside the way they make discoveries, working alongside them to build innovative use cases that push the boundar

Work Flexibility: Hybrid Position summary: This role will support a wide range of products across multiple surgical specialties, with a primary focus on post-market design support and product performance. Working closely with Quality, Marketing, Operations and Regulatory Affairs, you will investigate customer complaints, field returns and product performance trends to identify opportunities for improvement and support implementation of design changes. Product Engineering offers a unique opportunity to learn how medical devices perform throughout their entire lifecycle. You will develop deep product knowledge by working on real-world engineering challenges, gaining firsthand experience of how products are designed, manufactured, used by customers and perform in the field. Through investigation of product issues and implementation of improvements, you will help enhance product quality, reliability and customer experience, while contributing valuable insights that influence future product enhancements and next-generation designs. What you will do: Support post-market design activities for commercially released medical devices, helping to ensure products continue to meet customer, quality and regulatory requirements. Investigate customer complaints, field returns and product performance issues using structured problem-solving and root cause analysis techniques. Partner with Quality, Marketing, Operations and Regulatory Affairs to identify opportunities for product improvements and support implementation of design changes. Plan and execute engineering testing, verification and validation activities to evaluate product performance and support proposed design improvements. Support Nonconformance (NC), Corrective and Preventive Action (CAPA), and Engineering Change Request (ECR) activities while maintaining compliant engineering do

We are now looking for a Senior Performance Verification Engineer! As a member of our CPU Performance verification Team, you will be responsible for performance correlation, analyzing workloads and benchmarks for performance bottlenecks, developing microbenchmarks and creating the necessary verification infrastructure for performance analysis. This position offers you the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of outstanding people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. What you’ll be doing: Technical leadership role to define/plan/implement/execute performance verification strategy of sophisticated CPU designs Ability to delve into lowest level details of CPU unit design specification, implementation and it's performance impact Interactions with architect and design engineers to define detailed scope of micro architectural features Draft detailed performance testplans and define/Create scalable micros to validate features Analysis and correlation of CPU benchmarks/workloads Build infra/tooling needed for efficient performance correlation debug Ability to lead and provide detailed technical guidance to junior engineers Agility to work on multiple tasks/projects What we need to see: BS or MS in EE/ECE or equivalent experience. PhD is a plus 5+ years of experience in CPU performance modeling, performance correlation, performance analysis, or relevant experiences Strong understanding in CPU micro architecture and designs Experience with workload analysis and characterization Strong coding skills in scripting l

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Our team is seeking to extend the internship of our current AI Research Intern for the TAO (Train, Adapt, Optimize) Multi-Modal Model Development project, recognizing their exceptional performance and strong alignment with the team’s research goals. Their innovative ideas and technical contributions have significantly enhanced our work. Given the rapidly evolving field of multi-modal AI, encompassing vision-language modeling, universal segmentation, and large-scale model training, extending this internship will provide further growth opportunities for the intern while strengthening our team’s capacity to develop scalable, high-impact AI solutions. Embark on an exciting journey with NVIDIA, a global leader in AI and accelerated computing. As an AI Research Intern focusing on multi-modal AI and vision-language model development within the TAO framework in Hanoi/HCM City, Vietnam, you will be at the forefront of advancing cutting-edge machine learning research. You’ll collaborate with a talented team of engineers and researchers dedicated to developing state-of-the-art deep learning models for tasks such as image segmentation, cross-modal understanding, and universal representation learning. This internship offers a unique opportunity to contribute to next-generation AI systems with real-world impact across industries—from autonomous vehicles to intelligent content understanding. What you'll be doing: Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems. Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. Collaborate with cross-functional teams to integrate your research into production-le

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Drive risk strategy for company-level strategic initiatives, which includes: partnering with the company’s product, legal, operations, sales, and partnerships teams to solve risk problems and ensure a positive user experience. Perform research and analysis to assess Stripe’s current risk performance and develop and prioritize long-term strategic plans for future growth. Increase business enablement, allowing the types of supportable merchants to safely grow at scale, continuously optimizing for efficiency and effectiveness, and stay hyper focused on a positive user experience. Challenge the status quo and provide multiple alternative solutions and key execution criteria. Execute special projects and provide ad hoc analyses as initiatives, products, risks, and opportunities are constantly evolving. Who you are Minimum requirements Must have a Bachelor's Degree or foreign equivalent degree in Law, Business, Policy, Development Studies, or a related field, plus five (5) years post-bachelors, progressive related work experience as a Risk Strategist or a related occupation. Must also have five (5) years of experience in each of the following: Developing risk strategies and solutions and working with technical products, including working with product and engineering, and operations teams for implementation; Distilling complex, ambiguous risk and policy problems into clear guidance for internal sta

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brain of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As a NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is looking for an AI Computer Engineer to join its NVIDIA Infrastructure Specialists (NVIS) team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI factory systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyse, define and implement large scale AI Factory projects. The scope of these efforts includes a combination of Networking, System Design and Automation while being the face to the customer. What you will be doing: Primary responsibilities will include deploying, managing, and maintaining AI infrastructure for new and existing customers. Be the domain expert with customers during planning calls through implementation. Handover-related documentation and perform knowledge transfers required to support customers as they begin rolling out some of the most sophisticated systems in the world! Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements. What we need to see: Bachelor’s degree in computer science, Electrical Engineering, or a related field, or equivalent experience.