Engineering Lead Analyst in United States

Software Engineer (Associate or Experienced) Company: The Boeing Company The Boeing Company has an exciting opportunity for a Software Engineer to join the SATCOM Mission Planning Software Engineering team in Colorado Springs, CO. Our teams are currently hiring for a broad range of experience levels including; Associate and Experienced Software Engineers. The Satellite Communication (SATCOM) Mission Planning team is a critical part of the U.S. military’s nuclear command, control, and communications (NC3) network, providing nuclear-survivable connectivity. Our team develops software tools and services for advanced satellite and ground systems. This role offers the opportunity to work in a fast-paced development environment using modern, scalable technology and tools. Our team works in an Agile and CI/CD environment with automated testing, vulnerability scanning, and quality scanning capabilities. Position Responsibilities: Develops and maintains requirements, architecture, algorithms, interfaces, and designs for high-performance APIs between front-end and back-end software services Supports software development activities in an Agile environment using DevSecOps methodologies, including integration of completed software components into a fully functional software system Supports the development of critical features and support the full development lifecycle from design through deployment Builds, architects, and consumes APIs and backend services as part of the platform ecosystem, with an emphasis on automation, testing, and security Conducts code reviews to maintain code quality, enforce best practices, and ensure compliance with establis

PWI R&D Writing Systems Engineer Description - A Writing Systems Engineer is an experience individual contributor responsible for owning system-level performance of industrial inkjet web presses , with a strong emphasis on hands-on engineering, on-press troubleshooting, and technical leadership . This role leads complex problem solving across ink, printhead, media, firmware, and mechanical systems, driving print quality, reliability, and robustness through a combination of deep systems thinking and direct experimentation . The specialist serves as a key decision-maker in resolving ambiguous, cross-functional issues and ensuring successful product delivery. Responsibilities Hands-on system ownership & advanced troubleshooting (Primary) Serve as the technical owner for system-level performance , including print quality, reliability, and production robustness Lead hands-on troubleshooting on industrial web presses , diagnosing complex print defects (banding, mottle, nozzle behavior, edge effects, etc.) Design and execute on-press experiments (DOEs) to isolate root causes and quantify system sensitivities Drive root cause analysis across subsystems (ink formulation, printhead, firmware, mechanics, media) and implement corrective actions Support press bring-up, ramp, customer escalations, and field issues , often in high-pressure situations requiring rapid, data-driven decisions Translate real-world press behavior into actionable engineering insights and design improvements System design & integration leadership Define and develop system-level solutions to optimize ink/media interactions, printhead performance, and image quality Lead integration of subsystems (ink, printheads, m

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated

Ready to help developers and researchers get more from open AI models? At NVIDIA, our team improves support for leading community models such as Nemotron, Llama, Gemma, DeepSeek, and Qwen. As a Product Manager for Open Models, you will help coordinate model enablement, developer experiences, technical content, and product launches across NVIDIA’s accelerated computing platform. You will work alongside experienced product managers, engineers, model builders, and product marketing teams. This role is ideal for someone early in their product-management career who has a strong technical foundation, enjoys working across teams, and is excited about the open-model ecosystem. What you’ll be doing: Support collaboration with community model builders around model access, technical enablement, launch readiness, and go-to-market activities. Track emerging open-model releases and summarize their capabilities, technical differentiators, hardware requirements, and ecosystem impact. Maintain product requirements, launch plans, readiness checklists, and supporting documentation for assigned models. Partner with engineering, infrastructure, and developer-experience teams to support open models across inference, fine-tuning, evaluation, and deployment. Gather feedback from model builders and developers, identify recurring issues, and translate findings into actionable product requirements. Review and test developer workflows, sample applications, notebooks, and Python code used in demonstrations and technical content. Collaborate with product marketing on blogs, documentation, presentations, case studies, and social-media content. Support product announcements, demonstrations, keynote materials, and other high-visibility launches while working onsite at least three days per week. What we need to see: 2+ years of relevant experience in product ma

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. 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 brains 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 an 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. We are looking for an outstanding Compiler Engineer to help build the next generation of intelligent compiler technologies for NVIDIA's accelerated computing stack. Our team works at the intersection of compilers, agentic systems, numerical correctness, and verification to create systems that can reason about, generate, optimize, and validate code transformations across software and hardware boundaries. This is an excellent opportunity for new graduates who are excited about coding agents, AI-assisted software engineering, developer tools, and GPU computing. In this role, you will work with experienced engineers and researchers to build agentic systems and compiler-aware tooling that improve developer productivity, code quality, and system performance across NVIDIA's software and hardware stack. What you'll be doing: Build and improve coding-agent systems for tasks such as code generation, transformation, debugging, optimization, validation, and developer assistance. Develop agent workflows involving tool use, planning, memory, execution, and feedback loops for software engineering and compiler-related tasks. Help create training, evaluation, and verification environments to improve agent quality, correctness, r

We anticipate the application window for this opening will close on - 5 Oct 2026 Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life We are seeking a highly motivated Finance Forward Deployed Engineer (FDE) to join our Finance Analytics and Transformation team. This role sits at the intersection of Finance, Data, Analytics, Automation, and Artificial Intelligence. Unlike a traditional data engineering or analytics role, the Forward Deployed Engineer will work alongside Finance teams to deeply understand business processes, identify high-value opportunities, and rapidly design, deploy, and scale solutions that improve how Finance operates and makes decisions. The ideal candidate combines strong Finance and business acumen with hands-on technical capabilities. This individual will be comfortable participating in forecasting, planning, performance reviews, management reporting, and other Finance processes while also working directly with data, building analytical solutions, automating workflows, and applying emerging AI capabilities. The role requires a strong builder mindset: someone who can move from an ambiguous business problem to a working solution, partner with users to iterate quickly, and ultimately transition successful solutions into scalable enterprise capabilities. At Medtronic, we bring bold ideas forward with speed and

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T

Senior Product Manager, Robotics & Autonomy What we're doing isn't easy, but nothing worth doing ever is. At Diligent Robotics, we envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Our robots operate every day in hospitals, helping healthcare staff spend less time on routine work and more time caring for patients. Operating a real-world fleet gives us something few robotics companies have: continuous customer feedback and operational data that directly shapes the next generation of Physical AI. We're looking for a Senior Product Manager, Robotics & Autonomy to define and execute the product strategy for some of the most critical capabilities in our robotics platform. You'll work at the intersection of robotics, autonomy, AI, and software engineering to translate business priorities, customer needs, and technical opportunities into a clear product roadmap that drives measurable outcomes. This role is ideal for someone who understands complex autonomous systems and enjoys working alongside world-class engineers to bring ambitious technology from concept into production. Responsibilities Own the product strategy and roadmap for key Robotics and Autonomy initiatives, balancing customer impact, technical feasibility, and long-term platform investments. Define product requirements for autonomy, navigation, perception, fleet intelligence, simulation, and robotics platform capabilities. Partner closely with Engineering, AI, Robotics, Customer Success, Operations, and Leadership to align priorities across the organization. Translate customer feedback, fleet telemetry, and operational insights into product decisions that improve robot performance, reliability, and user experience. Prioritize investments using data, customer value, technical complexity, and business impact. Drive cross-functional execution from concep

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building high-performance AI systems and the supply chain required to deliver them at scale. We are looking for a Global Supply Chain Manager to own OSAT partnerships, backend manufacturing execution, and supply continuity from wafer-out through final shipment. This role is based in Santa Clara, CA; Austin, TX, or Toronto, ON, with regular travel to Taiwan and other Asia-based partner sites, approximately 25-30%. Candidates should be located near one of these hubs and able to work effectively across North American and Asia-Pacific time zones. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Bring 7+ years of experience in semiconductor supply chain, manufacturing, or supplier management, along with a bachelor’s degree in Supply Chain, Engineering, or a related discipline. Have a strong understanding of OSAT workflows, including flip-chip, wire bond, and wafer-level packaging, with hands-on experience working with Taiwan-based OSAT partners. Are comfortable negotiating complex supplier agreements, pricing, tooling, or NRE costs and managing relationships across technical, commercial, and operational issues. Are a clear, direct, a

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking an experienced Principal Hardware Diagnostics Engineer to design and develop diagnostics software used to monitor hardware health and diagnose system-level issues across Graphcore’s AI infrastructure platforms. This role focuses on building diagnostics agents, tools, and analytics frameworks that enable engineers and automation systems to identify, isolate, and resolve hardware issues across blade-level servers and rack-scale clusters. The Team Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. The Systems Engineering and Platform Validation team ensures Graphcore’s AI compute platforms are reliable, diagnosable, and operationally robust at scale. The team co

Manufacturing Test Engineer – Server Hardware Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. Role Overview We are seeking an experienced Manufacturing Test Engineer to support high-volume server manufacturing from board-level test through system-level production test. This role will work closely with an ODM manufacturing partner to define, implement, validate, and optimize the manufacturing test strategy for L6 board-level products , including ICT, MDA, and Board Functional Test , as well as support L10 system-level manufacturing test . The ideal candidate has strong experience in server hardware manufacturing, Linux-based test environments, diagnostic test coverage, fixture requirements, yield improvement, and root cause corrective action processes. This role requires both technical depth and hands-on manufacturing execution experience, with the ability to drive best practices across test development, factory readiness, quality planning, and ongoing production support. Key Responsibilities Manufacturing Test Strategy and Planning Work with ODM partners to define and execute the manufacturing test strategy for L6 board-level production . Develop and review test plans covering: In-Circuit Test, or ICT Manufacturing Defect Analyzer, or MDA Board Functional Test Diagnostic coverage requirements Manufacturing line test flow Fai

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

About the Team The Safety Training research team aims to fundamentally advance our capabilities for precisely implementing safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to train nuanced safety behaviors, how to make the model robust to bad actors, how to address privacy and security risks, and how to make the model trustworthy in safety-critical situations. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role We’re seeking a researcher to train and evaluate models for U.S. government use, with a focus on national security applications. You’ll advance safety post-training and robustness, helping models follow nuanced policies while preserving their usefulness and capabilities. In this role, you will: Research and implement methods for safety training, reinforcement learning, and adversarial robustness. Develop evaluations, identify model failure modes, and use findings to improve training. Work with research, engineering, security, and policy partners to support safe, reliable deployment. You might thrive in this role if you: Bring 4+ years of relevant AI safety research experience, including RLHF, adversarial training, or robustness. Have a degree in computer science, machine learning, or a related field, and strong deep learning research or engineering skills. Have experience improving model safety for deployment and enjoy collaborative research. Are motivated by OpenAI’s mission and the responsible use of AI in safety-critical settings. Security Requirements Active TS/SCI clearance or equivalent. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefi

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with