Technical Program Manager, Applied ML

Technical Program Manager, Applied Machine Learning

This role drives the end-to-end execution of the Applied Machine Learning team's initiatives: ensuring data quality, contributor marketplace efficiency, and extending horizontal ML capabilities across business units. You'll own program delivery from scoping to measurable adoption, while serving as the communication backbone across engineering, product, and leadership. You will be accountable for measurable outcomes: higher data quality, faster contributor onboarding, and adoption of horizontal ML capabilities across BUs.

You will manage the entire lifecycle of our cutting-edge GenAI initiatives, from initial scoping and prototyping to deployment of LLM-based techniques in production. This is a high-impact, cross-functional role requiring a deep understanding of ML engineering processes, risk management, and rapid iteration in a demanding AI environment. You will ensure the MLE team maintains focus, resolves dependencies, and rapidly delivers reliable, high-value ML solutions at scale.

You will:

• Own the end-to-end planning, scheduling, and execution for multiple GenAI ML programs, ensuring high-quality, on-time delivery against product goals.
• Collaborate closely with Product Managers and ML Engineers/Scientists to translate vision into clear, iterative execution plans.
• Ensure our ML systems move from prototype to production smoothly, by aligning engineering, research, and product teams around clear milestones, risks, and delivery standards.
• Translate technical complexity into concise, actionable updates for executive and cross-functional stakeholders. Drive clarity across teams by ensuring everyone understands priorities, risks, and outcomes.
• Proactively identify, track, and mitigate technical risks unique to GenAI development (e.g., model drift, prompt engineering evolution, data security/privacy, resource contention on large-scale compute).
• Manage dependencies and communication across core teams (e.g., Platform Infrastructure, Data Engineering, Product) to seamlessly integrate ML services into production microservice architectures.
• Provide clear, concise, and structured status reports to all stakeholders, including executive leadership, detailing project health, roadblocks, and delivery forecasts.

Ideally you'd have:

• 5+ years of experience as a Technical Program Manager or similar technical leadership role managing complex software or machine learning development projects.
• 2+ years of experience managing programs specifically focused on Applied Machine Learning, MLOps, or Data Science.
• Familiarity with the Generative AI lifecycle, including the application of LLMs (Large Language Models) for structured downstream tasks, model fine-tuning, and performance evaluation.
• Ability to reason about system architecture, data flow, and key technical challenges in building scalable ML services in cloud environments (e.g., using AWS, GCP, or similar microservice infrastructure).
• Experience with Agile methods and tools (e.g., Jira, Linear).
• Excellent verbal and written communication skills with a proven ability to translate complex technical challenges into clear program risks and business impacts for executive audiences.
• Interest in learning and engaging with modern ML/GenAI practices.

Nice to have:

• Hands-on familiarity with high-performance compute infrastructure for ML training and deployment in real-world products.
• Familiarity with data quality pipelines or internal evaluation frameworks
• Strong software engineering fundamentals, ideally having prior experience as an engineer or developer before transitioning into program management.
• Experience driving adoption of technical platforms across multiple product lines or business units.