Top Tech Jobs & Startup Jobs

Design and implement the car application that controls execution flow of software components on the Mobileye chip, manage sensor inputs (cameras, radar, vehicle signals), integrate data into algorithms to build a comprehensive vehicle worldview, work on real-time, automotive-scale systems, and collaborate across large software teams.

Lead end-to-end physical design for SoC blocks from RTL to GDS: floorplan exploration, synthesis, place-and-route, STA/timing closure, signoff (IR/EM, physical verification, LEC, low-power), and collaborate with front-end and architecture teams to optimize PPA.

Define and implement Linux/PCIe-based OS solutions for connectivity between EyeQ SoCs. Design SW stack for cross-chip communication, co-develop HW/SW with SoC architects, run performance analysis, PoCs, optimizations, and mentor kernel developers.

Lead end-to-end physical design for SoC blocks from RTL to GDS: floorplanning, synthesis, place & route, STA, signoff (IR/EM, physical verification, LEC, low-power), and collaborate with front-end and architecture teams to optimize PPA.

Design and develop software infrastructure and automation for Radar and LiDAR sensor platforms. Build scalable integration tools, automation pipelines, and system-level debugging to optimize performance across software, firmware, and specialized hardware accelerators. Collaborate with cross-functional teams to deliver robust production-ready sensing solutions.

Own the sim-to-real bridge for a full-size humanoid: build and maintain digital twins from CAD, model actuators from measured data, run system-identification campaigns, design domain randomization in Isaac Sim, manage deployment pipelines, generate synthetic data, and quantify and reduce the sim-to-real gap.

Design and own compact, high-current motor controller PCBs for humanoid robot joints from schematic to bring-up, including inverter stage, sensing, protections, encoder and sensor interfaces, MCU/communication PHY integration, high-density thermal layout, EMI/EMC support, and fast iteration with suppliers.

Design and improve ML-driven data curation pipelines for large autonomous-vehicle datasets: embedding extraction, VLM scene analysis, scoring, deduplication, sampling, GPU inference at scale, validation/diagnostics, dataset SDK and 3D geometry tooling, and collaborate with algorithm and infra teams to close data gaps.

Develop and train neural networks for object detection, scene understanding, and 3D perception in real-world driving. Design and analyze end-to-end deep learning pipelines, collaborate with algorithm/software/data teams to deliver production-ready models, and research novel computer-vision and multi-task learning methods to improve performance.

Design, verify, and validate DFT for autonomous-vehicle SoCs: develop HW/FW/SW for test, debug coverage/yield loss, use advanced DFT tools and methods for automotive safety (ISO26262).