ML Engineer: Inference Engine & Dev Experience Lead

Bazeta; Northern (KY); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Roboflow is seeking a Machine Learning Engineer to own and evolve the Inference engine and deployment pipeline. You will build, maintain, and scale production-grade ML systems while fostering open source contributions and strong customer enablement.

You will design automated reviews, triage, and end-to-end testing, enabling daily releases and rapid model integration across platforms. Collaboration with marketing, docs, and support will amplify impact.

Qualifications

• 5+ years of hands-on experience building and operating production-grade ML systems.
• Strong CV/ML foundation and understanding of inference in real-world deployments.
• Experience with open source contributions is a plus.

Responsibilities

• Build and maintain inference, our flagship CV engine, keeping it healthy and high-quality as contribution volume scales.
• Design an agentic-driven contribution pipeline — automated and semi-automated review, triage, and CI/CD.
• Develop a world-grounded test suite for nightly end-to-end runs across all targets.
• Define and enforce review standards and rules to guide agents and contributors.
• Streamline adding new models to inference to speed up deployments and usability.
• Teach internal teams and customers, enabling self-serve usage of inference features.
• Bridge core engineering and clients with docs, demos, and launches to improve adoption.
• Contribute to and grow the broader open source community around the project.

Skills

ML systems

Production deployment

Open source

CI/CD

Documentation

Job description

Roboflow is seeking a Machine Learning Engineer to own and evolve the Inference engine and deployment pipeline. You will build, maintain, and scale production-grade ML systems while fostering open source contributions and strong customer enablement.

You will design automated reviews, triage, and end-to-end testing, enabling daily releases and rapid model integration across platforms. Collaboration with marketing, docs, and support will amplify impact.