Software Engineer, Robotics

Scale AI Scale AI · Data AI · Mexico City, Mexico · 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. The role involves owning data processing pipelines, ML training/fine-tuning, and developing tools for data collection and evaluation, with a focus on real-time systems and data integrity.

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, C++), and frontend (React, TypeScript) stacks to build end-to-end solutions
  4. Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation
  5. Design comprehensive monitoring and evaluation frameworks for robotics models and data quality

Skills

Required

  • 3+ years of high-proficiency software engineering experience
  • strong background in complex systems
  • ability to independently research, analyze, and unblock hard technical problems
  • Strong programming skills in Python
  • Strong programming skills in TypeScript/Node.js for production systems
  • Experience with React and modern frontend development for 3D interfaces
  • Concurrent and real-time systems, with special attention to timing constraints
  • Understanding of distributed systems
  • Understanding of workflow orchestration
  • Understanding of cloud infrastructure (AWS, Temporal, Kubernetes, Docker)
  • Experience with databases (MongoDB, PostgreSQL)
  • Experience with data processing at large scale
  • Track record of working with cross-functional teams including ML engineers, researchers, and customers
  • Strong communication skills
  • 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
  • Background in SLAM
  • Background in motion planning
  • Background in imitation learning
  • Familiarity with autonomous vehicle data
  • Familiarity with lidar technologies
  • Familiarity with 3D data processing
  • Experience with ML model deployment and serving frameworks
  • Knowledge of teleoperation systems (ALOHA, UMI, hand tracking)
  • Knowledge of VR interfaces
  • Experience with workflow orchestration systems (Temporal, Airflow)
  • Published research or open-source contributions in robotics or autonomous systems

What the JD emphasized

  • Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity.

Other signals

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