Top Tech Jobs & Startup Jobs

Lead AI/ML safety engineering for Level 4 autonomous vehicles. Define SOTIF and functional safety strategies, derive requirements for learned systems, design runtime safety monitors and OOD detectors, assess dataset coverage and bias, analyze ML failure modes, and build evidence-backed safety cases. The role requires collaboration across perception, prediction, planning, systems, and safety engineering teams, with onsite work five days per week in Santa Clara, California.

Owns financial reporting, dashboards, KPIs, forecasts, budgeting, scenario analysis, and financial modeling. Partners with cross-functional teams to improve projections, supports consolidated financial statements, monthly and quarterly close, audits, compensation analysis, and Board and investor materials. The role reports to the CFO and is onsite five days per week in Santa Clara, California.

Develop and integrate embedded chassis-control software for autonomous vehicles and ECU hardware. Responsibilities include functional-safety development, model-based toolchain design, release planning, testing, vehicle bring-up, calibration, data analysis, debugging, and hardware/software integration. The engineer will validate AV components through on-vehicle, simulation, SiL, and HiL testing while collaborating with requirements, software, hardware, and systems engineers to support safe, reliable Level 4 autonomous vehicle operation.

Lead design and implementation of a multi-modal behavior prediction system using image and LiDAR data. Build optimized data pipelines, train and evaluate models (LSTM, Transformer), scale training/inference infrastructure, and integrate prediction into the autonomous driving stack. Drive R&D to production and ensure system reliability and safety through testing.

Design and implement real-time perception and sensor-fusion algorithms (LiDAR, camera, radar) for autonomous trucks. Build and optimize deep learning models, manage large-scale datasets, run field tests and simulations, and develop validation frameworks to ensure robust, safe perception in diverse driving conditions.

Build and improve HD mapping production pipelines: process and validate large LiDAR/camera datasets, extract road features, validate topology, develop Python geospatial tools, use PostGIS and cloud infrastructure, and collaborate with autonomy, perception, and planning teams to deliver high-quality maps on tight timelines.

Lead development and execution of test strategies and validation for autonomous vehicle control systems. Manage test engineers, develop automated testing frameworks, ensure traceability, troubleshoot integration issues, and scale HiL/ViL and vehicle-level validation infrastructure to guarantee safety and release quality.

Provide onsite day-to-day IT support for laptops, desktops, mobile devices, printers, and AV. Configure new-hire equipment and accounts, troubleshoot hardware/software/network issues, maintain inventory and perform routine security/connectivity checks, document processes, and coordinate with vendors for office infrastructure and networking support.

Design, build, and scale the AI platform for distributed multi-GPU training, experiment tracking, and model deployment. Optimize GPU clusters, networking (NCCL/InfiniBand), Kubernetes-native scheduling, and inference serving (TensorRT, Triton). Develop agentic automation for cluster health, CI/CD, and data curation while integrating ML lifecycle tooling and observability.

Integrate and maintain a ROS2-based autonomy stack inside high-fidelity simulators, author dynamic adversarial scenarios, configure simulated sensors, enable headless Docker orchestration for large-scale cloud testing, stream simulation states to a web dashboard, and manage serialized ROS2 message logging for analysis and playback.