Engineering Manager - Data Intelligence

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Engineering Leadership

Engineering Manager for Data Intelligence team focused on producing, curating, and leveraging high-quality data for autonomy development. Responsibilities include managing engineers, prioritizing data quality systems, labeling workflows, and data mining, and integrating foundation models to enhance these processes.

What you'd actually do

  1. Grow and manage a team of world-class engineers with the goal of delivering high-quality, well-labeled data and identifying critical edge cases for autonomy
  2. Prioritize development across data quality systems, intelligent labeling workflows, and large-scale data mining infrastructure
  3. Lead the integration of foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery
  4. Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles
  5. Set team goals and roadmap in alignment with training, evaluation, and deployment requirements

Skills

Required

  • engineering management experience
  • building and leading high-performing teams
  • building data quality systems, labeling pipelines, or annotation platforms at scale
  • modern ML infrastructure
  • data-centric AI approaches
  • foundation models for data automation

Nice to have

  • foundation models, including LLMs and VLMs, for data automation tasks
  • autonomous driving or robotics perception
  • active learning, auto-labeling, or human-in-the-loop ML systems
  • 3D perception data (camera, lidar, radar)

What the JD emphasized

  • 3+ years of engineering management experience
  • Experience building data quality systems, labeling pipelines, or annotation platforms at scale
  • Solid track record of building and deploying products

Other signals

  • leading a team
  • data quality systems
  • labeling pipelines
  • foundation models
  • ML iteration cycles