Ads ML Developer Experience Tech Lead

As part of the Ads AI Infra organization, our organization develops state-of-the-art AI/ML training technologies, enabling ML engineers to train, scale, and productionize cross-cutting ML model techniques. We are an engineering team with a strong hybrid ML and infrastructure skill set, dedicated to solving cross-layer and end-to-end ML infrastructure problems in the ads stack.

A key focus in this area is to improve velocity and efficiency for one of our most critical resources: machine learning engineers. This is a focus for the Ads-wide AI Modeling Velocity program.

We are looking for a Senior TL who is committed to being the champion for Developer Voice and driving the latest advancements in of large scale AI and ML infrastructure – you are excited about the transformative changes AI Agents will bring to software development!

Responsibilities

• Drive the technical direction and strategy of AI Developer Velocity efforts across the Ads Ranking AI organization
• Architects and evolve AI agent systems for model architecture research and development, including model, feature authoring agents and ML development ecosystem assistants
• Lead development of state-of-the-art AI/ML training technologies that enable ML engineers to train, scale, and productionize cross-cutting ML model techniques
• Champion Developer Voice by building tools and infrastructure that improve velocity and efficiency for ML engineers across the organization
• Define big-picture strategy for developer experience improvements and operationalize it into tactical execution plans
• Undertake ambitious technical projects in AI/ML infrastructure, compilers, build systems, and large-scale system design
• Mentor and lead engineers across the organization in ML infrastructure and developer tooling
• Partner with engineering managers and cross-functional partners to align on priorities and drive execution
• Present complex technical details in an intuitive and understandable way to leadership

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Deep and broad software engineering experience with a focus on machine learning infrastructure, developer tooling, or large-scale AI platform development
• Experience architecting and shipping AI infrastructure at scale that serves as a multiplier for other teams to drive impact
• Track record of defining technical strategy and driving cross-organizational alignment in developer experience or ML infrastructure
• Experience leading and mentoring engineers on complex technical projects
• Experience with large-scale system design, compilers, or build systems Experience with PyTorch or similar ML frameworks at production scale
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Track record of data-driven innovation in spaces where there are no existing clear answers
• Experience with AI agents, developer productivity tools, or machine learning platforms
• Experience driving adoption of relatively immature technologies to maturity and greater impact
• Contributions to developer tooling, ML infrastructure open-source projects, or published work in related areas
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies