Engineering Manager - Data Intelligence

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and valued at $15 billion, the company creates the digital infrastructure needed to bring intelligence to every moving machine on the planet. Serving the automotive, defense, trucking, construction, mining, and agriculture industries, Applied Intuition focuses on tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the U.S. military and its allies, rely on the company’s solutions. Headquarters are in Sunnyvale, California, with additional offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo.

The company operates in-office, with employees expected to work primarily from their Applied Intuition office 5 days a week. Flexibility is offered for occasional remote work or adjusted schedules to accommodate personal commitments.

About the Role

As an Engineering Manager on the Data Intelligence team, you will lead a world-class group of engineers focused on revolutionizing how high-quality data is produced, curated, and leveraged to accelerate autonomy development. Your team will work across three key areas:

• Data Quality: Build systems to measure, validate, and improve dataset integrity.
• Labeling Workflows: Design intelligent annotation pipelines combining human expertise with AI-powered automation.
• Data Mining: Surface rare, high-value driving scenarios from massive multi-modal fleet data.

You will drive the adoption of foundation models and cutting-edge AI techniques to scale these capabilities, set technical direction, and align team goals with model development, safety, and deployment milestones.

Responsibilities

• Grow and manage a team of world-class engineers to deliver high-quality, well-labeled data and identify critical edge cases for autonomy.
• Prioritize development across data quality systems, intelligent labeling workflows, and large-scale data mining infrastructure.
• Lead the integration of foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery.
• Evolve the data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles.
• Set team goals and roadmap in alignment with training, evaluation, and deployment requirements.
• Partner with research, autonomy, and data infrastructure teams to ensure high-quality, relevant, and diverse data powers models.
• Drive hiring, mentoring, and growth for a high-performing, mission-driven team.

Requirements

• 3+ years of engineering management experience.
• Passion for building and leading high-performing teams.
• Experience building data quality systems, labeling pipelines, or annotation platforms at scale.
• Familiarity with modern ML infrastructure and data-centric AI approaches.
• Understanding of how foundation models can be applied to automate data workflows.
• Solid track record of building and deploying products.

Nice to Have

• Direct experience with foundation models (LLMs, VLMs) for data automation tasks.
• Background in autonomous driving or robotics perception.
• Experience with active learning, auto-labeling, or human-in-the-loop ML systems.
• Familiarity with 3D perception data (camera, lidar, radar).

Benefits

• Comprehensive health, dental, vision, life, and disability insurance coverage.
• 401k retirement benefits with employer match.
• Learning and wellness stipends.
• Paid time off.

Pay

The base salary range for this full-time position is $204,000 - $343,000 USD annually. Compensation includes base salary, equity (options and/or restricted stock units), and benefits. The final offer will be influenced by experience, credentials, educational attainment, skill level requirements, interview performance, and the level and scope of the position.