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Scale AIScale AISan Francisco, CA

ML Systems Engineer, Robotics

Designs and builds scalable platforms for serving foundation models in robotics and autonomous vehicles. Requires 4+ years in ML infrastructure, backend systems, GPU optimization, and cloud technologies.

218k – 273k/yr
On-site4+ YOEML Engineering

About the role

You Will:

  • Build & Scale: Maintain fault-tolerant, high-performance systems for serving robotics-related models and foundation models at scale, ensuring low latency for real-time applications.
  • Platform Development: Build an internal platform to empower model capability discovery, enabling faster iteration cycles for research teams working on robotics.
  • Collaborate: Work closely with Robotics researchers and Computer Vision engineers to integrate and optimize models for production and research environments.
  • Design Excellence: Conduct architecture and design reviews to uphold best practices in system scalability, reliability, and security.
  • Observability: Develop monitoring and observability solutions to ensure system health and real-time performance tracking of model inference.
  • Lead: Own projects end-to-end, from requirements gathering to implementation, in a fast-paced, cross-functional environment.

Ideally, You'd Have:

  • Experience: 4+ years of experience building large-scale, high-performance backend systems, with deep experience in machine learning infrastructure.
  • Algorithm Optimization: Deep experience optimizing computer vision and other machine learning algorithms for cloud environments, including GPU-level algorithm optimizations (e.g., CUDA, kernel tuning).
  • Programming: Strong skills in one or more systems-level languages (e.g., Python, Go, Rust, C++).
  • Systems Fundamentals: Deep understanding of serving and routing fundamentals (e.g., rate limiting, load balancing, compute budgets, concurrency) for data-intensive applications.
  • Infrastructure: Experience with containers (Docker), orchestration (Kubernetes), and cloud providers (AWS/GCP).
  • IaC: Familiarity with infrastructure as code (e.g., Terraform).
  • Mindset: Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves:

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

Skills

KubernetesDockerPythonGoRustC++CUDAAWSGCPTerraform

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