Top Tech Jobs & Startup Jobs

Train, integrate, test, optimize, and monitor machine learning models and autonomy software on autonomous vehicles. Coordinate real-world vehicle testing, diagnose field issues, design data collection strategies, and develop tools and visualizations for analyzing behavior and control subsystem performance. The role requires robotics software development, sensor interface knowledge, Linux programming, and software debugging expertise.

Integrates hardware, software, and product requirements for an autonomous driving platform. Owns systems integration, validation, metrics, requirements specifications, verification criteria, FMEA analysis, and cross-functional trade-off resolution. Partners with system architects, controls teams, test and validation groups, and OEMs while evaluating regulatory requirements and improving engineering processes.

Design, train, and evaluate advanced machine learning models for autonomous driving, simulation, and ML platforms. Lead small cross-functional engineering teams, establish data and experiment practices for petabyte-scale training, address long-tail model failures, and work with multimodal datasets exceeding 100TB. The role requires commercial robotics experience, mentoring capability, expertise in VLA or generative world models, Python/PyTorch, sensor processing, and potentially edge deployment.

Leads architecture and development of production-grade mapping and localization ML systems for autonomous vehicles. Designs neural models for detection, segmentation, tracking, depth estimation, 3D reconstruction, and semantic mapping; owns data strategy, evaluation, deployment, and fleet validation. Mentors engineers, drives technical roadmaps, collaborates cross-functionally, and advances vectorized HD mapping, foundation models, and real-time optimization.

Leads the technical direction of an autonomous vehicle perception stack. Responsibilities include architecting scalable perception systems, developing scene detection and runtime activation, improving robustness against sensor degradation and adverse weather, integrating multimodal models, managing ML and data pipelines, monitoring field performance, leading testing and feature delivery, and mentoring engineers. Requires strong robotics, computer vision, machine learning, real-time systems, software architecture, and team leadership experience.

Lead definition, optimization, and validation of next-generation autonomous vehicle capabilities. Define and manage system-level requirements, design scenario-based tests in simulation and on-road, analyze real-world and simulation data, close coverage gaps, build KPI-driven reporting, and drive continuous improvement across cross-functional teams to ensure compliance with industry standards and robust validation coverage.

Lead vision, strategy, and technical roadmap for Behavior & Controls. Drive advances in MPDM, data-driven policies, simulations, learned reward functions, and control. Manage and grow engineering teams, set KPIs, coordinate cross-functionally, triage production issues, and deliver autonomy performance improvements.

Investigate fleet issues and perform root-cause analysis using vehicle logs; curate datasets; create and run simulation scenarios; report findings to autonomy teams; build documentation and knowledge base; support testing and escalation to improve AV safety and functionality.

Design end-to-end in-vehicle and vehicle-to-cloud communication architectures, including Ethernet, CAN/CAN-FD, LIN, and TSN. Architect OTA, telematics, SOA and middleware (Classic/Adaptive AUTOSAR, SOME/IP), ensure functional safety and cybersecurity compliance, evaluate trade-offs, perform FMEA, and collaborate with systems, software, and OEM partners to deliver secure, scalable AV communication systems.

The Director of System Safety oversees safety functions for autonomous vehicles, managing safety cases, deployment plans, and regulatory relationships while leading a multi-disciplinary safety team.