Develop and optimize a high-speed GPU-based simulation framework for ML training and validation. Apply reinforcement learning to solve behavior and path-planning challenges, bridge sim-to-sim and sim-to-real fidelity gaps, enable self-serve data generation for autonomy users, and write production-ready code integrating ML into core simulation architecture.
Simulation is essential for Zoox to rapidly iterate on our driving software and hardware, and to validate our safety before we drive in the real world. We create virtual worlds to challenge our robots, from real-world data, entirely novel scenarios, or a combination of both. Our simulations need to run at a huge scale to cover everything that might happen, and to help prove our driving to be safe.
As a Machine Learning Engineer on the Simulation Core Team, you will focus on the intersection of machine learning and synthetic environments within our high-speed, GPU-based simulation framework. Our success depends on you driving ML efficiency while solving complex "sim-to-sim" and "sim-to-real" fidelity gaps, ensuring our safety-critical models train on data that perfectly aligns with physical vehicle behavior.
In this role, you will:
- Develop and optimize our GPU-based simulation framework to support complex machine learning training and validation pipelines.
- Apply reinforcement learning concepts to solve complex behavioral and path planning challenges in simulation environments.
- Identify and resolve "sim-to-sim" and “sim-to-real” fidelity gaps to ensure parity between high-speed ML simulations, high-fidelity 3D environments, and physical vehicle execution.
- Build systems that allow autonomy users to self-serve data generation and accelerate their training iterations.
- Write robust, production-ready code to integrate advanced ML algorithms directly into our core simulation architecture.
Qualifications:
- PhD or Master’s in computer science, robotics, machine learning, or a related field.
- Deep understanding of reinforcement learning and its application in simulated or robotic environments.
- Hands-on experience developing, training, and fine-tuning deep learning models using modern frameworks (e.g., JAX or PyTorch).
- Strong proficiency in C++ and Python for building and deploying production machine learning systems.
- Experience analyzing and bridging fidelity gaps between synthetic training data and real-world execution.
Bonus Qualifications:
- Experience with GPU programming (CUDA) or high-performance compute clusters.
- Automotive or autonomous robotics industry experience.
- Strong background in deterministic systems and latency optimization.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Follow us on LinkedIn
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Zoox Seattle, Washington, USA Office
1111 3rd Ave, Seattle, WA, United States, 98101
Similar Jobs
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Handle inbound calls and warm leads to assess customers’ insurance needs, recommend appropriate Property and Casualty coverages, and convert prospects into policyholders. Representatives receive paid training and licensing support, work remotely, maintain customer-focused communication, and meet sales goals through persuasive consultation. The role requires a flexible schedule of four weekdays and one weekend day, with evening shifts for at least six months.
Top Skills:
PcWired High-Speed Internet
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Owns the Small Commercial Product AI investment roadmap and portfolio from intake and prioritization through execution, adoption, and performance measurement. Drives cross-functional AI initiatives, coordinates with Product, Data Science, Technology, and AI enablement teams, establishes business cases and KPIs, supports responsible AI governance, and promotes adoption of AI tools. Requires strong program management, stakeholder influence, analytical expertise, and knowledge of insurance product, pricing, underwriting, and predictive modeling.
Top Skills:
AIEmblemExcelPowerPointPredictive ModelingSASSQL
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Handle inbound calls and warm leads, assess customers’ insurance needs, recommend appropriate Property and Casualty products and coverages, and convert prospects into policyholders. The role includes paid training and licensing, customer-focused sales, brand representation, schedule flexibility, and remote work requirements. Representatives must meet performance goals, communicate persuasively, maintain strong organizational skills, and work four weekdays plus one weekend day on assigned shifts.
Top Skills:
PcWired High-Speed Internet
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
