Machine Learning Engineer - FT Freelance - America/Europe

Role Overview

We are seeking a skilled Machine Learning Engineer with a focus on systems and infrastructure engineering to support our embodied AI research and production systems. You will be responsible for building and maintaining the robust, high-performance infrastructure that underpins our robotics software stack, data infrastructure, and machine learning training platform.

Responsibilities

• Robotics Systems Software: Design and implement low-level robotics services, real-time control protocols, and sensor integration layers. Work directly with hardware to ensure deterministic, high-throughput performance on Linux-based robotics platforms.
• ML Platform & DevOps: Architect and operate our training infrastructure, including Kubernetes-based HPC clusters, multi-tenant GPU orchestration, distributed training job scheduling, and model deployment pipelines. Transition research code to production readiness and maintain efficient compute operations at scale.
• AI Training Automation: Convert research prototypes into automated, monitored, and reproducible training pipelines. Manage experiments, checkpoints, artifacts, and build tooling for rapid research progress while ensuring production reliability.
• Data Storage: Develop and maintain large-scale data ingestion systems to capture and track multimodal robotics data, ensuring reliability, versioning, and reproducibility across terabytes of data.
• Data Pre-processing: Design pipelines for preprocessing multimodal robotics data to feed into training systems, handling data transformation, normalization, and quality assurance to provide clean inputs for model training.

Required Skills

• Proficiency in at least one systems language such as C, C++, or Rust, and fluency in Python.
• Extensive experience with Linux systems programming, POSIX APIs, and handling real-time constraints.
• Proven experience in building data pipelines or infrastructure at scale.
• Familiarity with Kubernetes, distributed systems, and HPC environments.

Nice to Have

• Knowledge of JavaScript or Go.
• Ability to bridge the gap between algorithms and production systems.
• Strong debugging skills across various layers including firmware, OS, networking, and applications.
• A keen interest in working within a fast-paced research environment that supports breakthroughs in robotic intelligence.