Top Tech Jobs & Startup Jobs in San Francisco, CA

Design, implement, benchmark, and optimize CUDA-based GPU kernels and custom operators for on-vehicle ML inference. Build profiling, debugging, and validation tooling, collaborate with compilers, runtime, and architecture teams to deliver high-performance libraries into production, and manage internal customer relationships while maintaining high engineering standards.

Lead camera ISP tuning and evaluation for autonomous vehicles: define specs, perform objective/subjective image quality tests, tune ISP and sensors (AE, AWB, HDR, noise reduction, tone mapping), collaborate with hardware, embedded, and ML teams, and support validation, vendor integration, and production readiness.

Technical leader who architects and delivers end-to-end ML and computer vision pipelines to reconstruct and maintain map primitives from multi-modal vehicle sensor data, driving national-scale, production mapping systems and cross-functional integrations.

Lead design, development, and deployment of state estimation, localization, and sensor calibration systems for onboard autonomous vehicles. Architect scalable, robust real-time solutions, mentor engineers, drive technical roadmaps, and integrate capabilities across multidisciplinary teams to support safety-critical autonomous driving.

Build and optimize scalable analytics frameworks and tooling to accelerate autonomous vehicle development, testing, and deployment. Implement automation for test creation, data collection, and performance monitoring; create extensible C++/Python shared libraries; collaborate with simulation, data infra, and AV engineering to enable rapid model feedback and maintain high code quality.

Develop and evolve the model compilation toolchain to convert high-level ML models into optimized inference artifacts for vehicle accelerators. Architect compiler passes and analyses to improve build times, memory, and latency. Collaborate with kernels, runtime, and hardware teams, and build validation, regression detection, and diagnostics tooling to ensure correctness, performance, and reliability for on-vehicle deployment.

Design, develop, and deploy state estimation, localization, and sensor calibration systems for autonomous vehicles. Build validation, continuous monitoring, CI/regression tests, simulation scenarios, and prototyping/debugging tools. Collaborate with cross-functional teams and influence technical roadmaps to integrate localization and sensor alignment into AV systems.

Develop 2D and 3D simulation platforms for autonomous mobile robots, create realistic scenarios and edge cases, integrate navigation software, debug simulated robot behavior, analyze results, and build regression testing workflows. Collaborate with robotics and AI teams to improve system validation and robustness. Required expertise includes Python or C++, robotics simulation platforms, physics or game engines, ROS 2, and core robotics modules such as localization, mapping, and planning.

Leads strategy, validation, and safety assurance for Level 3–4 autonomous driving behaviors powered by machine learning. Owns the behavior-focused safety case, ODD decomposition, evaluation metrics, safety targets, and launch-readiness evidence across simulation, closed-course, and public-road testing. Collaborates with AI, software, simulation, validation, and vehicle teams while hiring and developing a high-performing AV safety engineering team.

Lead design and implementation of scalable distributed backend systems and data pipelines for national-scale autonomous vehicle mapping. Own architecture, deployment, performance, and cross-functional delivery while mentoring engineers and driving system reliability and interoperability.