Simulation Engineer Jobs

The Core Data Science team builds the products and data assets that let teams across Zoox measure and improve the autonomy and operational performance of our fleet. In this role, you'll focus on fleet simulation — the environment our data teams use to develop, test, and evaluate the algorithms that orchestrate our autonomous fleet (dispatch, routing, and vehicle assignment) and to understand how those algorithms perform before they reach the road. You’ll piece together the constituent components into a coherent, easy-to-use simulation environment, filling in the gaps, and building generalizable mechanisms so data scientists can measure their algorithm's impact on fleet efficiency. You'll join a diverse, experienced team with rapidly growing scope while working with one of the industry's most valuable autonomous vehicle datasets. In this role, you will: Turn existing fleet-simulation components into a coherent, self-service environment that data scientists and ML engineers can run without deep software expertise. Fill gaps and build the connective tissue between simulation, data, and fleet-orchestration algorithms. Build generalizable mechanisms that let teams measure how their orchestration algorithms affect fleet efficiency. Collaborate with data science, ML, and fleet-orchestration teams to shape and prioritize the simulation roadmap. Establish best practices and processes around simulation, evaluation, and data-driven decision-making. Qualifications Software development experience in a production environment, with fluency in Python; or demonstrated experience learning new programming languages. Experience building tools, services, or frameworks that make complex systems usable by non-specialist users. Familiarity with any version control system, with preference for Git. Experience designing metrics and building mechanisms that deliver robust, actionable insights. Good communi

The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras. This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans. In this role, you will: Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines. Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities. Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation. Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy. Mentor engineers and interns, and establish best practices for training and deploying ML on Zoox sensor data. Qualifications: 2+ years of prior experience as a Technical Lead 5+ years of experience developing ML models in Python with PyTorch or TensorFlow <

Senior Software Engineer, Agent Simulation and Evaluation — US, CA, Santa Clara. Apply via Workday.

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role We are seeking a Principal Systems Engineer to lead the use of modeling and simulation throughout the aircraft design process. This person will develop integrated aircraft-level simulations, evaluate design alternatives, and translate analysis into clear engineering decisions. The role requires close collaboration with the aerodynamics, structures, propulsion, electrical, controls, and vehicle systems teams. The ideal candidate combines strong technical depth in aircraft simulation with the leadership and communication skills needed to drive multidisciplinary design decisions. Key Responsibilities Own the architecture, development, and validation of integrated aircraft simulations. Use simulation to guide aircraft configuration, subsystem sizing, requirements, and design trade studies. Integrate aerodynamic, structural, propulsion, electrical, mass-properties, controls, and mission-performance models. Lead multidisciplinary design optimization and sensitivity analyses. Quantify design margins, uncertainty, risk, and system-level impacts of proposed changes. Define simulation fidelity requirements appropriate to each phase of development. Establish model verification, validation, configuration-management, and documen

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Simulation is at the core of autonomy development. The Simulation team is responsible for building the simulator that powers all simulations at Nuro, allowing us to develop and test our autonomous driving technology with confidence. The team focuses on solving many novel simulation problems with innovative and creative solutions - from synthesizing sensor data and automated scenario generation, to performance and resource optimization, to framework and interface design - collaborating with teams across the company to set and expand the range of what’s possible to simulate. About the Work Expand the functionality, performance, and usability of our simulator. Develop innovative solutions to improve simulation realism and coverage through synthesis. Design and build solutions to unify and simplify the interactions of complex systems. Work across a large array of potential efforts, ranging from new greenfield projects to expandi

Air Proprietary 2 Hardware Engineering Manager - Flight Simulation Labs — USA - Berkeley, MO. Apply via Workday.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. In this position, you will be joining a brilliant team to collaborate with Micron’s various design and verification teams all over the world, support the efforts of design verification flow development, optimization, and implementation and work with cross-functional team to assure the best cost, quality, reliability, time-to-market, and customer satisfaction We are seeking a talented CAD senior engineer specialized in analog and digital simulations to join our high-achieving engineering team. As a CAD senior engineer, you will play a pivotal role in optimizing and simulating complex analog and digital circuits, contributing to the development of state-of-the-art products that shape our industry. You will get a chance to develop the industry's first and unique flows to enhance productivity and reduce pre-silicon failures. Responsibilities: Work closely with memory design teams and solve their daily challenges and provide complete solutions for the future. Proactively identify problem areas for improvement, propose, and develop innovative solutions. Develop highly scalable, and clean software systems. Continuously evaluate and implement new tools and technologies to improve the current software flows. Work with EDA vendors to evaluate and integrate E

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Mach Industries is seeking a New Graduate Guidance, Navigation, and Controls (GNC) Engineer to support the development of next-generation autonomous defense systems. In this role, you will help design, simulate, test, and integrate algorithms that enable our vehicles to navigate, maneuver, and complete their missions. You will work closely with flight software, avionics, aerodynamics, propulsion, systems, and flight-test teams to take GNC capabilities from early simulation through hardware testing and flight. Key Responsibilities Develop and test guidance, navigation, and control algorithms for autonomous aircraft and missile systems. Build simulations and models to evaluate vehicle dynamics and system performance. Support the development of flight-control laws, guidance algorithms, navigation filters, and state-estimation methods. Analyze flight and test data to evaluate performance and identify opportunities for improvement. Support software-in-the-loop, hardware-in-the-loop, ground, and flight testing. Integrate GNC algorithms with flight software, sensors, actuators, avionics, and propulsion systems. Perform Monte Carlo simulations and sensitivity analyses across different operating conditions. Document algorithms, simulation results, test p

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our robotics team is growing and we are looking for a Software Engineer to join our Sensor Data and Calibration team. We are searching for an engineer with robotics and machine learning expertise to develop synthetic sensor simulation models and algorithms. The ideal candidate has hands-on experience in the research, development, and implementation of machine learning methods (e.g., NeRF or Gaussian splatting) for generating synthetic sensor data (photorealistic images, realistic lidar and/or radar, etc.). About the Work Research, develop, and implement state-of-the-art synthetic sensor simulation methods Analyze and characterize the realism and utility of synthetic sensor data Answer critical questions about sensor data and autonomy performance Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements Role is scoped as a Senior/Staff IC with the flexibility to grow into

Job Details: Job Description: In this role, you will lead cross-functional collaboration to advance circuit simulation and modeling capabilities for advanced foundry technologies. Your responsibilities will include: Vendor collaboration: Partnering with EDA vendors to enhance and validate industry-standard simulation tools and design flows. Technology alignment: Working closely with technology leaders, VLSI physical design teams, and PDK teams to ensure simulation and modeling capabilities are aligned with roadmap needs. PDK readiness: Driving readiness of high quality simulation and modeling solutions so they are available in time for PDK delivery. Qualifications: You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Minimum Qualifications: Bachelor’s degree in electrical engineering or computer engineering or related engineering discipline with 12&#43; years or master’s degree in electrical engineering or a related discipline and at least 10 years of industry experience in the semiconductor field; or Ph.D. in Electrical Engineering or a related discipline with a minimum of 8 years of industry experience in the semiconductor field. 5&#43; years supporting circuit simulation tools and working with circuit simulation vendors to develop solutions. 5&#43; years collaborating with EDA vendors on optimizing circuit simulation and modeling for advanced technology nodes. 3&#43; years of hands-on experience with BSIM or other compact models for transistor modeling at advanced nodes (e.g., FinFET, GAA).</

Build the systems that deliver Simulation Technology knowledge to developers, partners, internal teams, and the AI agents that increasingly sit between them and our documentation. Our KnowledgeOps team sets the information architecture and quality standards for Omniverse, Isaac Sim, and OpenUSD documentation. You'll build the automation, pipelines, and AI-ready infrastructure that apply those standards at scale, and work with documentation leads to refine the architecture based on what you learn. You're a writer who builds: as comfortable in Git, CI, or Python as in a style guide, and fluent with LLMs in daily work. We build systems where the right way is easier than the wrong way. For you, that means turning documentation, standards, and tribal knowledge into tooling, templates, and self-service paths, so fewer people have to ask &#34;how do I…?&#34; What you'll be doing: Collaborate with documentation leads on knowledge architecture, sharing implementation feedback (what works, breaks, and scales) to refine content models, information architecture, and AI-readiness patterns Build and run docs-as-code pipelines: Git authoring, CI/CD builds, linting, link and code-sample validation, and publishing Make knowledge AI-ready: structure and package content for RAG, internal assistants, and agentic workflows, including llms.txt, MCP-accessible sources, agent skills and context kits, and evaluation sets for answer accuracy Automate the content lifecycle with LLMs and scripting, from drafting and updating to auditing, with checks for freshness, code accuracy, and terminology drift, and human review where judgment matters Encode standards (user stories, release readiness, onboarding, security guidance) into templates, validators, and guided workflows rather than static documents Capture tribal knowledge from engineering, product, and operations, and turn it into playbooks, decisi

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 6+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu

Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise. Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members. What you’ll do: Lead teams to design and implement flight control algorithms for electric VTOL aircraft Work cross functionally to connect GNC requirements with other system requirements Influence leadership with decisions that are affected by GNC systems. Implement creative solutions to efficiently verify complex systems and software Build simulations to verify and validate system requirements Run trade studies to inform aircraft design and system architecture Work with the Flight Test team to design tests that safely evaluate the vehicle capabilities Improve the fidelity and capabilities of our vehicle and environment simulation models Analyze full-scale and subscale flight data to improve our models Author software requirements and test cases that drive the design of the GNC software Collaborate with Systems Engineering to properly decompose higher level requirements Collaborate with Systems Safety and Systems Engineering to identify and correct any deficiencies in the Flight Control System. What you need: Strong knowledge of vehicle dynamics, optimization, and both classical and modern control theory BS in Aerospace Engineering, Electrical/Computer Engineering, or a related field with at least 10 years of relevant experience OR MS with at least 8 years of relevant experience OR PhD with at

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Overview This role focuses on using process and defect simulation methodologies to systematically identify defect root causes (true RC) and enable process window optimization . As part of the RDA / Yield Engineering organization, you will work on high-impact projects that connect process physics, simulation results, and manufacturing data to improve process capability and final product yield. This is an exciting opportunity for engineers passionate about linking simulation with real fab problems and turning modeling insights into measurable manufacturing improvements. Responsibilities Develop and apply process / defect simulation models to understand defect generation mechanisms across key wafer fabrication steps. Correlate simulation results with inline defect, EBI, process data, and yield indicators to identify true root causes of defects. Drive data-backed process optimization strategies to expand process windows and improve yield and reliability. Perform what-if simulations to evaluate the impact of process parameter changes, material variations, or equipment conditions. Partner with process, integration, and equipment engineers to translate simulation insights into fab-implementable actions . Lead or support defect reduction, yie