Top Tech Jobs & Startup Jobs

Lead multi-disciplinary engineering projects from concept through delivery, coordinate cross-functional teams (Engineering, Design, Product, Customer), manage complex releases and milestones, engage customers for requirements, adjust timelines and resources, and ensure successful completion of deliverables and metrics.

Lead strategic sourcing for Physical AI hardware (GPUs, edge compute, sensors) for autonomous defense platforms. Develop RFx and long-term procurement strategies, partner with engineering on SWaP-C requirements, ensure FAR/DFARS/DCMA/CPSR compliance, negotiate with suppliers, reduce cost, and drive process improvements across global supply chains.

Conduct research on 3D vision and generation topics (e.g., world-action foundation models, multi-modal pretraining, Gaussian splatting) for autonomous driving and robotics. Collaborate with research scientists and engineers to develop methods, write high-quality publications, and contribute to deploying models into real autonomous systems using company infrastructure and fleet data.

Conduct cutting-edge research in reinforcement learning and VLA post-training for autonomous driving and robotics. Publish at top conferences, collaborate with engineers to test and deploy algorithms, and scale large closed-loop RL systems using industry ML infrastructure.

Conduct research on 3D vision and generation (foundation models, multi-modal pretraining, Gaussian splatting) for autonomous driving and robotics; publish at top conferences; collaborate with research engineers to test and deploy algorithms in autonomy and simulation products.

Design and implement full-stack, infrastructure, robotics, and graphics software for autonomy products. Own technical decisions, work closely with users, and build features and tools that accelerate customers' autonomy development workflows.

Lead program management for multiple automotive engagements from Tokyo: define milestones, run sprints and roadmaps, manage Tier-1/2 suppliers, act as primary OEM contact, align cross-team technical roadmaps, drive issues to closure, and support international rollouts for ADAS/embedded software through series production.

Lead architecture and implementation of the L4 trucking fallback stack. Define interfaces to perception, behavior, planning, and control; design degraded-driving and minimal-risk maneuvers; specify algorithms to detect autonomy degradation and trigger fallbacks or remote intervention; integrate with remote assistance; collaborate across teams and provide technical leadership.

Build and maintain large-scale cloud simulation infrastructure across AWS, GCP, and Azure. Improve deployment reliability, monitor and resolve bottlenecks, optimize CI/CD and developer tooling, and ensure interoperability with customers' autonomy software.

Develop and implement ML-first perception, prediction, or planning capabilities for autonomous vehicles. Build end-to-end deep learning models, production software, and integrate ML workflows with Applied Intuition products. Collaborate on evaluation, deployment, and model optimization for real-world autonomy systems.