Staff Technical Project Manager, ADAS

Cariad, Inc.•Mountain View, CA

10h•Hybrid

About The Position

We are CARIAD, an automotive software development team with the Volkswagen Group. Our mission is to make the automotive experience safer, more sustainable, more comfortable, more digital, and more fun. To achieve that we are building the leading tech stack for the automotive industry and creating a unified software platform for over 10 million new vehicles per year. We’re looking for talented, digital minds like you to help us create code that moves the world. Together with you, we’ll build outstanding digital experiences and products for all Volkswagen Group brands that will transform mobility. Join us as we shape the future of the car and everyone around it. Role Summary: The Staff Technical Project Manager for Automated Driving leads the planning activities for CARIAD’s US-based automated driving workstream, with a primary focus on ML-driven L2++ / L3 capability development, integration, and validation. This role supports the local engineering teams developing core automated driving capability and ensures tight coordination across model development, data workflows, evaluation, system integration, and in-vehicle deployment. In addition to program management, this role also acts as the agile delivery lead for the team: driving execution cadence, facilitating prioritization and planning, removing blockers, and helping the team operate effectively in a fast-moving and ambiguous environment. Furthermore, this role helps enable the effective use of GenAI and agentic AI for development by coordinating tooling access, infrastructure readiness, and local adoption formats in partnership with engineering, IT, and other support functions. The Staff Technical Project Manager serves as a key coordination bridge across US and international engineering teams, ensuring milestones, dependencies, interfaces, and decisions are clearly owned and executed. Alongside technical execution, this role maintains visibility across program risks, resource needs, and budget topics, and ensures leadership has clear, actionable reporting.

Requirements

Strong communication and stakeholder management skills across organizations, geographies, and time zones.
Strong ability to structure ambiguous problem spaces into milestones, owners, dependencies, and decision points.
Proven cross-functional delivery across engineering, platform, integration, and partner teams.
Ability to operate effectively in a fast-moving environment with evolving technical scope.
Creates clarity & momentum by aligning people, processes, and systems; anticipates and removes impediments.
Strong understanding of ADAS/automated driving development, including system integration and the interfaces between model development, validation, and vehicle integration.
Experience managing technically complex programs involving machine learning, embedded systems, autonomy, or robotics.
Experience operating in an Agile environment, including backlog management, sprint planning, dependency management, and team facilitation.
Working knowledge of tools for program execution and reporting (e.g., Jira, Confluence, dashboards) and disciplined risk/issue management.
Master’s degree in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field
12+ years of experience in applied machine learning, deep learning, robotics, or automated driving
5+ years of experience in one or more of the following: multimodal foundation models, computer vision, reinforcement learning, imitation learning, or AD/ADAS systems

Nice To Haves

Experience enabling adoption of modern engineering productivity tooling, including AI-assisted development workflows (GenAI/agentic AI) across technical teams.
Experience coordinating compute/tooling needs for ML development (training/inference infrastructure, data pipelines, evaluation tooling).
Familiarity with automotive safety and quality concepts relevant to ADAS/AD development (e.g., ISO 26262, ASPICE).
PhD in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field
Strong candidates with equivalent industry experience will be considered

Responsibilities

Own program structure, milestones, dependency management, and risk tracking for the US automated driving development program.
Coordinate cross-site dependencies with partner engineering teams; ensure interface contracts, deliverables, and integration handoffs are explicit and tracked.
Help translate evolving engineering work into a clear and executable delivery plan, balancing near-term milestones with longer-term capability build-up.
Drive execution across model development, data workflows, evaluation, system integration, and in-vehicle deployment.
Ensure integration readiness through clear entry/exit criteria, validation plans, and tracked closure of integration issues.
Align system-level interfaces, build integration plans, and coordinate multi-team delivery for vehicle releases.
Establish and run the team’s execution cadence, including planning, backlog refinement, dependency tracking, and regular progress reviews.
Act as Agile Delivery Lead / Scrum Master by facilitating ceremonies, improving team operating rhythm, identifying blockers early, and driving timely resolution.
Support prioritization decisions and maintain a healthy, actionable backlog aligned to program milestones.
Maintain structured reporting and clear escalation paths for engineering and leadership stakeholders.
Track program actuals versus plan across headcount, compute, tooling, and supplier support; surface deviations early and support planning decisions.
Own RAID (risks, assumptions, issues, dependencies) discipline and drive mitigation plans to closure.
Enable effective use of GenAI and agentic AI development tools by coordinating access, tooling, infrastructure, and process readiness with internal partners.
Drive local AI productivity initiatives such as workflow pilots, hackathons, and best-practice sharing to improve engineering efficiency and effectiveness.