Engineering Manager - Data Intelligence

About the role

As an Engineering Manager on the Data Intelligence team, you will lead a high‑performing group of engineers who build and scale systems that ensure the quality, labeling, and discovery of data used to train autonomous vehicle models. The team works across data quality, intelligent labeling pipelines, and large‑scale data mining to accelerate autonomy development.

Key responsibilities

• Grow and manage a team of engineers delivering high‑quality, well‑labeled datasets and identifying critical edge cases.
• Prioritize development of data quality measurement tools, AI‑enhanced labeling workflows, and data mining infrastructure.
• Integrate foundation models (LLMs, VLMs, multimodal models) to automate labeling, quality assurance, and scenario discovery.
• Evolve the data engine architecture to scale high‑fidelity labels, reduce annotation costs, and speed up ML iteration cycles.
• Set team goals and roadmap aligned with training, evaluation, and deployment milestones.
• Collaborate with research, autonomy, and data infrastructure teams to ensure data integrity and relevance.

Required profile

• Proven experience leading engineering teams in data‑intensive or AI‑focused environments.
• Strong track record of delivering complex, scalable data pipelines and infrastructure.
• Ability to translate product and safety requirements into technical roadmaps.
• Excellent communication and stakeholder‑management skills.

Required skills

• Experience with foundation models such as Large Language Models (LLMs), Vision‑Language Models (VLMs), and multimodal AI.
• Deep understanding of data quality assurance, labeling automation, and large‑scale data mining.
• Proficiency in building and operating high‑throughput data pipelines.

What we offer

• Competitive compensation and equity package.
• Opportunity to shape the data foundation for next‑generation autonomous systems.
• Collaborative, in‑office environment with occasional remote flexibility.