ML Systems Engineer (Robotics)

TL;DR

ML Systems Engineer (Robotics): Designing and building scalable platforms for serving foundation models tailored for physical agents with an accent on GPU optimization and high-performance backend systems. Focus on optimizing computer vision algorithms, ensuring low latency for real-time applications, and bridging the gap between AI research and production.

Location: San Francisco, CA

Salary: $227,200 - $284,000 USD

Company

Scale AI develops reliable AI systems for critical decision-making, providing high-quality data and full-stack technologies for leading models.

What you will do

• Maintain fault-tolerant, high-performance systems for serving robotics and foundation models at scale.
• Build an internal platform to accelerate model capability discovery for research teams.
• Collaborate with Robotics researchers and CV engineers to optimize models for production and research.
• Perform architecture and design reviews to ensure system scalability, reliability, and security.
• Develop monitoring and observability solutions for real-time model inference performance.
• Lead end-to-end projects from requirement gathering to implementation.

Requirements

• 4+ years of experience in large-scale high-performance backend systems and ML infrastructure.
• Deep expertise in GPU-level algorithm optimizations (CUDA, kernel tuning) for cloud environments.
• Proficiency in systems-level languages such as Python, Go, Rust, or C++.
• Strong understanding of serving and routing fundamentals (load balancing, concurrency, rate limiting).
• Experience with Docker, Kubernetes, and cloud providers (AWS/GCP).
• Familiarity with infrastructure as code (Terraform).

Nice to have

• Exposure to Vision-Language-Action (VLA) models.
• Knowledge of high-performance video processing (FFmpeg, NVDEC/NVENC) or 3D data (point clouds).
• Familiarity with robotics middleware (ROS/ROS2) or AV data formats.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Equity compensation grants.
• Retirement benefits and a learning and development stipend.
• Generous PTO and commuter stipend.
• Inclusive and equal opportunity workplace culture.