Top Tech Jobs & Startup Jobs

Lead technical product management for Mobileye's autonomous vehicle features: define roadmaps, elicit requirements, set data-driven KPIs, coordinate cross-functional teams and external OEM partners, support pre-sales and onboarding, and ensure product quality and performance.

Lead end-to-end system architecture and integration for a full-size humanoid robot: define DOF, torque/mass targets, kinematics, compute and power architecture; arbitrate cross-domain trade-offs; drive roadmap, milestones, prototyping, vendor buy-vs-build decisions; absorb program management; hire and mentor the engineering team.

Lead end-to-end deep learning R&D for computer vision in autonomous driving: design and implement models, research state-of-the-art methods, improve existing algorithms, own project execution, and mentor team members while collaborating cross-functionally.

Lead definition and implementation of Linux/PCIe-based OS solutions for high-bandwidth connectivity between EyeQ SoCs. Design and implement the SW stack for cross-chip communication, collaborate on SW/HW co-development with SoC architects, run performance analysis, PoCs and optimizations, and mentor kernel development engineers.

Develop end-to-end deep learning models for computer vision in autonomous driving. Responsibilities include problem formulation, data analysis, model design, training, evaluation, optimization, and deployment, working on new projects with production impact.

Own solution architecture for cloud-connected automotive features: engage customers, define system and software requirements, align with hardware/software, plan timelines, lead cross-functional teams, and ensure ASPICE-compliant quality from concept to commercialization.

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.

Develop and validate actuator-level control algorithms for each humanoid joint: FOC and commutation, current/velocity/position/torque loop design, torque estimation, friction/cogging compensation, observers, safety/fault handling, guide embedded implementation on motor controller PCB, run joint dyno characterization tests, and deliver validated actuator models and limits to Sim2Real and RL teams.

Engage customers to gather requirements and define cloud communication system architecture. Derive system and software requirements, plan timelines, prioritize features, and lead cross-functional teams. Ensure quality by adhering to ASPICE and systems engineering practices, and bridge embedded/Linux environments with cloud backends. Support customer engagements, travel as needed, and collaborate with software architects, developers, and project managers to commercialize features.

Build and improve ML-driven data curation pipelines for large-scale autonomous-vehicle datasets: embedding extraction, scene detection, GPU inference orchestration, scoring, deduplication, sampling, dataset validation, SDK/tools, and collaboration with algorithm and infra teams to ensure balanced, high-quality training data.