Machine Learning Engineer - FT Freelance - America/Europe: Confidential (Recruited via Arc.dev)

This is a freelance, full-time contract (40 hours/week) for a duration of 12 weeks. The company is seeking a skilled Machine Learning Engineer with a strong focus on systems and infrastructure engineering to support their embodied AI research and production systems.

You will be responsible for building and maintaining the robust, high-performance infrastructure that underpins their 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 training infrastructure, including Kubernetes-based HPC clusters, multi-tenant GPU orchestration, and distributed training job scheduling.

AI Training Automation: Convert research prototypes into automated, monitored, and reproducible training pipelines.

Data Storage: Develop large-scale data ingestion systems to capture and track multimodal robotics data across terabytes of storage.

Data Pre-processing: Design pipelines for preprocessing multimodal robotics data (transformation, normalization, QA) to feed into training systems.

Requirements
Experience: 5+ years of relevant experience.

Languages: Proficiency in at least one systems language (C, C++, or Rust) and fluency in Python.

Systems: Extensive experience with Linux systems programming, POSIX APIs, and handling real-time constraints.

Infrastructure: Proven experience building data pipelines at scale and familiarity with Kubernetes, distributed systems, and HPC environments.

Nice to Have
Knowledge of JavaScript or Go.

Strong debugging skills across firmware, OS, networking, and applications.

Ability to bridge the gap between algorithms and production systems.