Forward Deployed Engineer – Physical AI

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Take charge of discovery, technical scoping, infrastructure design, construction, and production deployment for key customer and ISV collaborations.

• Develop and manage cloud infrastructure for simulation, training, evaluation, inference, and batch processing tasks.

• Create platform services for job execution, scheduling, retries, observability, logging, access control, and cost management.

• Incorporate Nebius cloud services into customer product experiences.

• Construct secure, isolated, observable, and dependable onboarding infrastructure for pilots.

• Enhance cloud cost efficiency, utilization, performance, and reliability.

• Troubleshoot issues across application, network, storage, compute, and orchestration levels.

• Collaborate with Physical AI Systems and Platform & Product FDEs via APIs, SDKs, and product workflows.

• Assist in defining infrastructure architecture for multi-tenant SaaS, enterprise deployments, and high-throughput physical AI workloads.

• Transform recurring customer infrastructure challenges into reusable platform functionalities.

• Utilize AI coding tools to expedite production engineering.

• Co-author reference architectures, solution templates, and technical blogs; maintain feedback channels with Field CTO, Product, and Engineering teams.

⛳️ Requirements

• Minimum of 6 years of hands-on engineering experience in backend, cloud infrastructure, platform engineering, or SRE.

• At least 2 years of experience in a customer-facing or deployment-centric technical role.

• Proficiency in building distributed systems, job orchestration, compute platforms, internal developer platforms, or ML infrastructure.

• Strong programming skills in Python, Go, or similar backend languages.

• Proficiency in Claude Code, Codex, and Cursor for AI-native development.

• Experience with Kubernetes, containers, CI/CD, observability, cloud networking, storage, IAM/RBAC, and infrastructure as code.

• Familiarity with GPU workloads, batch jobs, training pipelines, inference tasks, or HPC-style computing environments.

• Proven capability to troubleshoot infrastructure issues across application, network, storage, compute, and orchestration layers.

• Strong instincts for isolation, RBAC, uptime, and traceability.

• Excellent written and verbal communication skills.

• Applicants must have authorization to work in the country of application and provide proof of employment eligibility.

• Additional advantageous experience includes Forward Deployed Engineering, Nebius/AWS/GCP/Azure/Lambda Labs, Slurm/Soperator/Kubernetes GPU scheduling/Ray/Argo/Airflow/Metaflow, ML training infrastructure, enterprise clients, NVIDIA GPU infrastructure, CUDA, Isaac Sim, or Omniverse.

🏝️ Benefits

• Competitive salary packages.

• Opportunities for career advancement and learning.

• Flexibility and ownership in your role.

• A collaborative and innovative work culture.

• Chance to engage in significant AI projects.

• An international environment with talented teams.

• Trust and genuine ownership.

• Opportunity to influence the future of AI.