Developer Advocate for Physical AI

Dexmate Inc.; Fremont, Northern (CA, KY); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Dexmate Inc. is seeking an ML engineer to help AI/ML developers deploy models on robotic platforms. You will build sample projects, write tutorials, and own SDK documentation, turning research into practical deployments.

You will publish weekly technical content, answer developer questions, and publish integration guides. The role emphasizes delivering clear, reusable code and guiding engineers from signup to first impactful deployment.

Qualifications

• Fluent Python and real ML engineering experience, including training, inference, or MLOps.
• Interest in applying ML to physical AI and robotics.
• Proven track record of published technical content.
• Write clean, well-documented code engineers will reuse.
• 3+ years of ML engineering experience.
• Consistent content output schedule.

Responsibilities

• Build and publish sample projects showing AI/ML engineers how to train, fine-tune, and deploy models on the Dexmate platform.
• Write and publish weekly technical tutorials—architecture explainers and deployment guides for ML engineers new to physical AI.
• Own the SDK documentation for AI/ML workflows, including quickstart guides and API references.
• Answer developer questions daily in Discord and GitHub Discussions within 24 hours.
• Build reference integrations with foundation AI model providers and publish architecture guides.
• Speak at AI/ML conferences (3–4 times per year) such as NeurIPS, ICLR, ICML, CoRL.
• Run live demos for developers, partners, and enterprise prospects.
• Surface model integration friction and missing platform capabilities to engineering weekly.

Skills

Python

ML engineering

Model training

Documentation

Technical writing

Education

Bachelor's in CS/ML

Tools

Git

Jupyter

PyTorch

Job description

Dexmate Inc. is seeking an ML engineer to help AI/ML developers deploy models on robotic platforms. You will build sample projects, write tutorials, and own SDK documentation, turning research into practical deployments.

You will publish weekly technical content, answer developer questions, and publish integration guides. The role emphasizes delivering clear, reusable code and guiding engineers from signup to first impactful deployment.