ML Software Engineer
Job Summary
The Staff Software Engineer - Machine Learning will join the Smart Agents group to build ML models and systems simulating road users for autonomous vehicle testing. Responsibilities include developing ML and reinforcement learning models, streaming optimization, integration, and creating ML infrastructure for production deployment. The ideal candidate brings strong software engineering expertise and experience in robotics, simulation, or latency-sensitive backend services.
Responsibilities
- Develop ML and reinforcement learning models and training loops
- Streamline integration and create ML infrastructure and data pipelines
- Contribute strong software engineering expertise to the ML team
- Support AV technologies including Autopilot and Lane Keep
Required Skills
- 4+ years in robotics or latency-sensitive backend services
- Experience with ML frameworks (TensorFlow, PyTorch)
- Strong programming in modern C++ or Python
- Experience deploying perception/prediction/AV models
Job Details
Role: The Smart Agents group is responsible for building the ML models and system to simulate road users in a variety of situations and generate the scenarios used for testing and training AV driving policies. If you think of Simulation as a video game our autonomous vehicles train on to learn to drive, the Smart Agents team develops the ML/AI models that control the other characters in the video game to interact in realistic ways as the av drives-eg, the other vehicles, bikers, and pedestrians. Our technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL) policies. The Smart Agents group work closely with the rest of the Simulation, and our partners Behaviors, Perception, and Safety Engineers. The specific duties may include ML/RL model development as well as training loop development, streamlining optimization, integration, creating ML infrastructure, metrics, and data pipelines for production model deployment as well as for fast experimentation cycles.
What You'll Do:
- Support the team in developing machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization.
- Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation.
- Work as part of an ML team and contribute strong software engineering (SWE) expertise.
- Support the team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies.
- Experience in simulation and robotics is highly desirable.
Your Skills & Abilities:
- 4+ years of experience in the field of robotics or latency-sensitive backend services.
- Background working with machine learning teams, algorithms, and models, including reinforcement learning and sequence prediction.
- Familiar with ML frameworks such as Tensorflow or PyTorch.
- Strong programming skills in modern C++ or Python.
- Experience with profiling CPU and/or GPU software, process scheduling, and prioritization.
- Passionate about self-driving car technology and its impact on the world.
- Expertise in setting architectures that are scalable, efficient, fault-tolerant, and easily extensible.
- Track record in deploying perception/prediction/av models into real world environments.