Software Engineer, Robotics & Autonomous Systems

Scale AI Scale AI · Data AI · San Francisco, CA · AVCV / Robotics EPD

Software Engineer focused on building production systems for robotics data collection, model training pipelines, and evaluation infrastructure within Scale AI's Robotics business unit, contributing to the development of embodied AI systems.

What you'd actually do

  1. Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets
  2. Build ML training and fine-tuning pipelines using Scale's robotics data
  3. Work across backend (Python, [Node.js](http://node.js), C++) and frontend (React, TypeScript) stacks to build end-to-end solutions
  4. Develop tools and systems for robotics data collection, teleoperation, and model evaluation
  5. Design comprehensive monitoring and evaluation frameworks for robotics models and data quality

Skills

Required

  • 3+ years of software engineering experience in robotics, autonomous vehicles, or related fields
  • Strong programming skills in Python and TypeScript/Node.js for production systems
  • Experience with React and modern frontend development for 3D interfaces
  • Practical experience with robotics frameworks (ROS/ROS2), simulation environments, or AV systems
  • Understanding of distributed systems, workflow orchestration, and cloud infrastructure (AWS, Temporal, Kubernetes, Docker)
  • Experience with databases (MongoDB, PostgreSQL) and data processing at scale
  • Track record of working with cross-functional teams including ML engineers, researchers, and customers
  • Strong communication skills and ability to operate with high autonomy

Nice to have

  • Experience with C++
  • Experience with robotics hardware platforms (robotic arms, mobile robots, perception systems) with a focus on time synchronization
  • Background in computer vision, SLAM, motion planning, or imitation learning
  • Familiarity with autonomous vehicle data, lidar technologies, or 3D data processing
  • Experience with ML model deployment and serving frameworks
  • Knowledge of teleoperation systems (ALOHA, UMI, hand tracking) or VR interfaces
  • Experience with workflow orchestration systems (Temporal, Airflow)
  • Published research or open-source contributions in robotics or autonomous systems

What the JD emphasized

  • production systems
  • robotics data collection
  • model training pipelines
  • evaluation infrastructure
  • embodied AI systems
  • ML training and fine-tuning pipelines
  • robotics data
  • real-time systems
  • monitoring and evaluation frameworks
  • ML engineers and researchers
  • system reliability and performance
  • production systems
  • robotics frameworks
  • distributed systems
  • workflow orchestration
  • cloud infrastructure
  • data processing at scale
  • cross-functional teams
  • ML engineers
  • researchers
  • customers
  • high autonomy

Other signals

  • building production systems for robotics data collection
  • model training pipelines
  • evaluation infrastructure
  • embodied AI systems