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Lead and manage the AI Data Engine team, focusing on ML dataset generation and acceleration of data pipelines while collaborating with cross-functional teams.

Develop and maintain simulation, analysis, debugging, visualization, and rerun tools for autonomous driving software. Build high-performance C++ tools and Python backend tooling, enable parameter overrides and local or cloud-based execution, and create GUI or web-based visualizers for step-through behavior analysis. Collaborate with planning and controls engineers, optimize tool performance, and support automated root cause analysis across complex autonomy codebases.

Drive cross-functional software and hardware release planning and execution across autonomy integration, engineering, operations, and testing teams. Track release metrics, manage configurations, maintain release calendars and documentation, coordinate priorities and dependencies, remove blockers, and report risks. Partner with engineering leadership on organizational objectives, retrospectives, and continuous process improvement.

Develop trajectory generation and motion planning algorithms for production autonomous vehicles. Responsibilities include trajectory optimization, performance-critical C++ software development, simulation and testing, code and design reviews, collaboration with planning, prediction, and controls teams, technical roadmap development, and mentoring junior engineers. The role requires expertise in MPC, numerical optimization, vehicle dynamics, control, and autonomous driving systems.

Design and improve autonomous vehicle features, define system behaviors and performance targets, and collaborate across product, autonomy, operations, testing, and safety teams. Develop validation and verification suites using software integration, simulation, HIL, and closed-course testing. Establish performance monitoring, conduct safety analyses, perform root-cause investigations, and recommend corrective actions for issues found during testing or road operations.

Defines and verifies the operating domain for autonomous robotaxi deployments, collaborates with autonomy, mapping, infrastructure, and operations teams, and develops AI-powered tools to assess expansion opportunities. The role includes analyzing system performance, validating map releases against constraints, documenting tools, supporting testing and coverage analysis, and contributing to the safety case for commercial launch. Requires strong Python, SQL, visualization, version control, software development, data analysis, and communication skills.

Supports corporate and product strategy for autonomous vehicle systems and platform expansion. Develops strategic roadmaps, evaluates market and technology opportunities, conducts transportation and regulatory research, analyzes KPIs, collaborates with Engineering and Finance, and prepares executive presentations and shareholder communications. The role is based in Boston and requires regular in-office work.

Senior Counsel will provide corporate, commercial, privacy, compliance, claims, litigation, and employment-law support. Responsibilities include negotiating agreements, advising on CCPA/CPRA and data protection, managing governance templates, handling vehicle incident claims and employment disputes, and partnering with Operations, Commercial, HR, and Engineering. The role requires onsite work in Las Vegas five days weekly and approximately 10% travel.

Owns design release, engineering integration, and OEM orchestration for automotive HMI and UX hardware. Translates UX concepts into technical requirements, manages engineering documentation, BOMs, validation plans, ECNs, supplier relationships, and vehicle integration. Leads DVP&R, design readiness reviews, risk mitigation, and technical program communication while coordinating component maturity through DV, PV, and PPAP milestones.

As a Machine Learning Systems Engineer, you will optimize distributed training systems, enhance performance profiling, and develop high-performance GPUs for machine learning workloads.