Teams at Gatik

Develop, optimize, and deploy production machine learning models for autonomous vehicle perception, prediction, planning, and scene understanding. Own the full ML lifecycle, build scalable training and data pipelines, optimize neural networks with quantization and TensorRT, and integrate models into C++ vehicle systems. Analyze simulation and real-world driving data, improve reliability and latency, and collaborate with autonomy, hardware, systems, and infrastructure teams.

Own the functional safety lifecycle and system safety concepts for a Level 4 autonomous driving platform. Lead hazard analysis, STPA, FMEA, fault tree analysis, requirements traceability, safety metrics, and minimum-risk maneuver architecture. Define fail-operational and fail-safe strategies across perception, localization, mapping, planning, controls, and fault management. Collaborate with software, middleware, infrastructure, and systems teams to support safe autonomous releases.

Lead Gatik’s end-to-end verification and validation architecture for autonomous vehicle systems. Own the V&V framework, Verification Traceability Matrix, safety-case evidence, and driverless release sign-offs across SIL, HIL, track, and public-road testing. Govern testing strategies, ensure requirements traceability, coordinate cross-functional teams, and prepare audit-ready validation packages aligned with UL 4600, ISO 26262, and ISO 21448.