Collaborate with multiple ML teams across vision, LLM and speech to architect ML application code that reduces technical debt and time to delivery.

Develop and maintain data utilities for various text, image, speech data and ensure flexibility to new data.

Automate verification and testing of ML models on RDU.

Architect, develop and maintain evaluation benchmark infrastructure for ML models across modalities.

Coordinate ML release process with compiler, runtime and other complementary software team releases to ensure smooth production delivery.

Set software standards (testing, code structure, gotchas, error handling, oncall) for ML teams working with complementary software teams; lead by example and codify these into code and documentation.

10+ years experience contributing to large codebases and architecting software infrastructure

10+ years experience as tech lead unblocking engineers by diving into code

Strong and principled software and code review practices

5+ years experience with open-source ML Frameworks, e.g., PyTorch, Tensorflow

2+ years experience building engineering tools to enable iterative ML Research and Development

Familiarity with design decisions behind common developer tools in the community (e.g. HuggingFace, FastAI, Pytorch Lightning, Mosaic ML

Experience developing, training and large scale ML models (LLMs, LVMs, CV, etc) is preferred.

Proven track record of managing complex projects across different teams/orgs.

Proven success in hiring, onboarding, performance management, goal setting and related processes for the team.

B.S, M.S. or PhD in Computer Science or a related field