ML Infrastructure Engineer
We’re supporting a client with the recruitment requirement outlined below. If your recruiting expertise and networks align with the role, please 'apply' to express your interest.
Once approved to work on the opportunity, you’ll receive the full brief, including the client name, role details, and commercial terms.
Role Details
Company: US-based robotics and AI startup
Location: Redwood City, California
Employment Type: Full-time
Work Arrangement: On-site, 5 days a week
Salary: $220,000–$320,000, with flexibility for exceptional candidates
Experience: 5+ years
Visa Sponsorship: Available
About the Company
An advanced robotics company developing general-purpose robots powered by proprietary AI models. Its technology is already deployed in commercial environments, including hospitality and restaurant industries.
The company is backed by leading technology investors and brings together experienced engineers and researchers from major AI, technology, and autonomous systems companies.
About the Role
The company is hiring an ML Infrastructure Engineer to build and optimise the infrastructure supporting large-scale machine learning training.
This role focuses on distributed training systems, GPU clusters, and high-throughput data pipelines for multimodal AI models. The ideal candidate combines strong software engineering skills with hands-on experience operating large-scale ML training infrastructure.
Responsibilities
Build and optimise distributed ML training infrastructure across GPU clusters.
Improve training performance using PyTorch Distributed, FSDP, CUDA, and NCCL.
Manage cluster scheduling, orchestration, and failure recovery.
Profile GPUs and troubleshoot multi-node performance bottlenecks.
Develop high-throughput pipelines for multimodal sensor data.
Improve infrastructure scalability, reliability, and training efficiency.
Collaborate with research and engineering teams to support advanced AI model development.
Requirements
5+ years of infrastructure or software engineering experience.
Proven ownership of large-scale distributed ML training systems.
Hands-on experience with PyTorch Distributed, FSDP, GPU sharding, CUDA, and NCCL.
Experience operating research compute clusters using SLURM or Kubernetes.
Experience working with real-world sensor or multimodal data, such as video, audio, and robotics data.
Strong programming and software engineering fundamentals.
CS or related technical degree from a strong program
Willingness to work on-site in Redwood City five days a week.
Interview Process
Candidate submission and hiring manager review.
Recruiter screening.
System design interview.
Practical coding interview.
Second coding interview.
Behavioral and cultural fit interview.
Offer and hiring.
🌍 Remote from anywhere in the globe
Workplace, Culture & Diversity
Corporate culture is essential to allow the organization to differentiate itself. In terms of image on the one hand, it has strengths both internally and externally to consumers. It is indeed a source of cohesion and motivation of employees and it limits conflicts. With customers, it conveys a positive image and can develop a feeling of closeness to the company or even become a criterion of choice.
About Fractal Talent
We Are Fractal Talent, a global community of freelance and fractional recruiters. We provide recruiting expertise to our clients as a virtual extension of their teams, deployed on an embedded, project or per role basis, and matched to client need. Top tier quality, unrivalled flexibility.
If you're a recruiter, come join a community that acts as your outsourced sales function. We align your skills to our clients - with the aim to enrich quality recruiters and enable a far greater flexibility in how you manage your career.