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Forward Deployed Engineer – Physical AI
Nebius GroupForward Deployed Engineer focusing on Physical AI systems and workflows for strategic clients. Collaborating with internal teams to ensure successful implementation and model improvement in real-world applications.
Posted 7/2/2026full-timeRemote • California, Texas • 🇺🇸 United StatesMid-LevelSenior💰 $169,900 - $254,900 per yearWebsite
Tech Stack
Tools & technologiesDistributed SystemsPythonPyTorch
About the role
Key responsibilities & impact- End-to-End Ownership Inside Strategic Accounts: Own discovery, technical scoping, system design, build, and production rollout for each design partner and ISV engagement.
- Physical AI Workflows & Pipelines: Build and own physical AI workflows across real-world data, synthetic data, model training, evaluation, deployment, and failure capture.
- Evaluation & Failure Loops: Design scenario-based evaluation workflows, regression testing, failure analysis, and before-versus-after model comparisons.
- Customer Data & Integration: Work with customer datasets including video, images, telemetry, annotations, simulation outputs, and deployment logs.
- ISV Integration Development: Stand up custom technical integrations with key Physical AI ecosystem partners.
- Pattern Codification & Productization: Identify which prototypes contain generalizable abstractions worth hardening into modular product components.
- Rapid Engineering Velocity: Use modern AI coding tools as primary leverage.
- Field Enablement Contributions: Co-author high-value technical artifacts that arm the broader Nebius SA and sales field.
- Feedback Loops to Product: Maintain structured channels to ensure customer learnings flow back to the Field CTO, Product, and Engineering teams.
- Technical Eminence: Represent Nebius at customer engineering deep-dives, ISV technical co-build sessions, and industry events.
Requirements
What you’ll need- 6+ Years of Hands-On Engineering: Experience in applied ML, physical AI, computer vision, robotics, simulation, autonomy, or AI/ML platforms, with at least two years in a customer-facing or deployment-oriented technical role.
- Real ML Systems Beyond Notebooks: Demonstrated track record building data pipelines, training pipelines, evaluation harnesses, model versioning, deployment, and monitoring that real users have depended on at meaningful scale.
- Strong Python & ML Frameworks: Strong Python engineering skills and hands-on experience with PyTorch or similar ML frameworks.
- Evaluation & Model Improvement Instinct: Practical understanding of evaluation, metrics, failure analysis, data quality, and model improvement loops.
- Multimodal Data Fluency: Experience working with video, image, telemetry, annotation, and multimodal datasets.
- AI-Native Development Workflow: Fluent in modern AI coding tools and treat them as primary leverage.
- GPU & Distributed Systems Fluency: Strong working knowledge of GPU compute, distributed training infrastructure, high-throughput storage systems, and orchestration frameworks.
- Customer-Facing Engineering Maturity: Comfort working directly inside customer environments, shipping code on someone else's infrastructure.
- Prototype Mindset: Strong instinct for the 80/20 of prototype engineering.
- High Agency: Navigate ambiguity in complex organizations without waiting for permission.
- Communication: Strong written and verbal communication skills.
Benefits
Comp & perks- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Applied MLPhysical AIComputer VisionData PipelinesModel VersioningDeploymentEvaluation HarnessesFailure AnalysisModel ImprovementAI-Native Development Workflow
Soft Skills
Strong CommunicationHigh Agency