About the job
You will serve as a strategic technical leader bridging the gap between AI algorithms, open source AI/ML tooling, and the Red Hat AI platform. In this high-impact role, you will architect the frameworks that enable novel AI Algorithms in areas like synthetic data generation, model training, and inference-time scaling.
Responsibilities
Define the technical strategy and architecture for AI/ML tooling and frameworks to work smoothly with platform components, ensuring scalability, resilience, and maintainability.
Serve as a Subject Matter Expert (SME) for the organization, advising leadership and stakeholders on the design of frameworks that drive community adoption and developer delight.
Mentor and coach Principal and Senior engineers, fostering a culture of technical excellence and helping to build specialized AI/ML tooling skills within the team.
Influence the broader open-source AI ecosystem by designing frameworks that make our tools popular in the community.
Champion and define the team's best practices for leveraging AI-assisted development tools to accelerate coding, testing, and documentation workflows.
Lead the development of complex projects on data generation, model training, inference-time scaling, and new algorithms.
Qualifications
Minimum
10+ years of software development experience, with significant experience architecting and building developer tooling for Machine Learning workflows.
Ability to work in the Boston MA office
Proven track record of maintaining or creating AI/ML projects, with a strong preference for popular Open Source projects or large-scale enterprise internal tooling frameworks.
Deep knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) and the developer pain points associated with the ML lifecycle.
Experience with Large Language Models (LLMs), particularly in the context of tooling, fine-tuning, or serving.
Demonstrated ability to identify and integrate the latest AI tooling frameworks and best practices into the organization to accelerate engineering efficiency.
Proficiency in at least one modern backend programming language (e.g., Python, Go, Rust) with a strong preference for languages common in the ML ecosystem.
Demonstrated ability to lead technical strategy for tooling frameworks or platform engineering teams.
Proven experience designing software frameworks or APIs that have achieved significant adoption.
Excellent communication skills, with the ability to influence Red Hat leadership and shape open-source strategy.
Proven track record of mentoring senior engineers and elevating the technical bar of an organization.
Preferred
Advanced programming expertise in Python, specifically related to the ML ecosystem (libraries, packaging, performance).
Experience with state-of-the-art post-training techniques.
Advanced degree (Master’s or PhD) in Machine Learning, NLP, or a related field.
Experience with Red Hat products.