Forward Deployed Engineer - Physical AI
New
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NebiusCloud AI Infrastructure
Remote - United StatesFull-TimeSenior
Salary169,900 - 254,900 USD per year
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Job Details
- Experience
- 6+ Years
- Required Skills
- PythonKubernetesMachine LearningPyTorchComputer VisionDistributed Systems
Requirements
- 6+ years of hands-on engineering experience in applied ML, physical AI, computer vision, robotics, or autonomy.
- At least two years of experience in a customer-facing or deployment-oriented technical role.
- Demonstrated track record building data pipelines, training pipelines, evaluation harnesses, and model monitoring at scale.
- Strong Python engineering skills and hands-on experience with PyTorch or similar ML frameworks.
- Practical understanding of evaluation, metrics, failure analysis, data quality, and model improvement loops.
- Experience working with video, image, telemetry, annotation, and multimodal datasets.
- Fluency in modern AI coding tools like Claude Code, Codex, or Cursor.
- Strong working knowledge of GPU compute, distributed training, and orchestration frameworks like Kubernetes, Ray, or Slurm.
- Strong written and verbal communication skills.
Responsibilities
- Own discovery, technical scoping, system design, build, and production rollout for each design partner and ISV engagement.
- Build and own physical AI workflows across real-world data, synthetic data, model training, evaluation, deployment, and failure capture.
- Design scenario-based evaluation workflows, regression testing, failure analysis, and before-versus-after model comparisons.
- Integrate NVIDIA ecosystem tools and develop custom technical integrations with key Physical AI ecosystem partners.
- Identify prototypes for modular product components and partner with Product and Engineering to integrate them into the core platform.
- Co-author technical artifacts such as reference architectures and solution templates to scale field knowledge.
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