Senior Principal Engineer- Autonomous Driving (ADAS) Data Loop & Flywheel
Core
Architecting and executing the end-to-end continuous data engine and AI flywheel for L2+ ADAS and autonomous driving stacks, managing the full lifecycle from raw fleet log ingestion to model retraining and validation.
Role type
Senior Principal Engineer (Autonomous Driving Data Loop & MLOps)
Builds
Automated data curation pipelines, active learning systems, auto-labeling frameworks, and production-grade training infrastructures for embedded automotive platforms.
Domain
Autonomous Driving / AI Systems / Embedded Automotive
Deliverable
production ML models
Required skills
End-to-End AI architecture, Deep Learning frameworks (PyTorch, TensorFlow), Model compression and quantization, Cloud-native distributed training, MLOps/CI/CD, Active learning, Fleet data loop automation, Embedded SOC deployment, Functional safety standards (ISO 26262, SOTIF)
Preferred skills
Offline high-precision auto-labeling frameworks, Closed-loop simulation engines (SIL/HIL), Synthetic scenario generation, Python and C++ programming
Technologies
Ray, Kubernetes, Triton, Spark, Transformers, Occupancy Networks, Vision-Language models
Responsibilities
Define technical roadmap for the E2E Autonomous Driving Data Engine; Oversee architecture and testing of the AI data flywheel; Collaborate with cross-functional leads to scale the AI machinery ecosystem; Establish rapid-evaluation frameworks for emerging AI solutions; Guide transition of research prototypes to scalable production pipelines; Implement automated validation workflows and scenario-based testing; Mentor and lead a high-caliber team of AI scientists and engineers.
Seniority
Principal, hands-on IC with strategic leadership
