ML Engineer, II - Simulation Enablement
Core
Build and scale the simulation platform (Torc Sim) to enable Autonomy teams to replay, recompute, evaluate, and visualize autonomous driving models at scale.
Role type
Senior Machine Learning Engineer (Simulation Enablement)
Builds
End-to-end data flow from data ops platform to simulation environment and persistent storage; scalable replay/recompute workflows and metric evaluation pipelines.
Domain
Autonomous driving / Robotics / Simulation
Deliverable
production ML models | product features
Required skills
Python, data pipelines at scale, simulation/replay/model validation, autonomy/robotics ML models (perception, tracking, prediction, planning), cloud storage and compute, cross-team communication, hands-on debugging
Preferred skills
Camera/Lidar/Vehicle Intent/Object Tracking models, visualization tooling (Foxglove, OpenGL, Three.js), large sensor data formats (MCAP, Parquet), distributed compute/orchestration (Ray, Anyscale, AWS HyperPods), Infrastructure-as-code (Terraform), CI systems (GitHub Actions)
Responsibilities
Act as embedded point of contact for Autonomy teams; implement end-to-end data flow; onboard models for replay/recompute workflows; ensure adoption of visualization tooling; become domain expert on partner models; debug full-stack issues; translate feedback into product roadmap requirements; document workflows for scaling adoption.
Seniority
Senior, hands-on IC
