Senior Product Manager, ML Enablement

About Etsy

Etsy is the global marketplace for unique and creative goods. We build, power, and evolve the tools and technologies that connect millions of entrepreneurs with millions of buyers around the world. As an Etsy Inc. employee, whether a team member of Etsy or Depop, you will tackle unique, meaningful, and large-scale problems alongside passionate coworkers, all the while making a rewarding impact and Keeping Commerce Human.

The base salary range for this full-time position is $164,000.00 - $212,000.00 USD per year. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy.

The Role: Senior Product Manager, ML Enablement

We are looking for a Senior Product Manager, ML Enablement to join our Machine Learning Enablement (MLE) organization. MLE builds the tools, platforms, and developer experiences that power every machine learning system at Etsy, enabling hundreds of scientists and engineers to train, evaluate, and deploy models that deliver value.

As a Senior Product Manager, ML Enablement, you’ll help build the next generation of Etsy’s ML platform: enabling faster ML developer velocity, improved reliability, and a more cohesive developer experience, ensuring our platform investments deliver measurable impact for ML practitioners.

For this role, we are considering candidates based in the United States. Candidates living within commutable distance of Etsy’s Brooklyn Office Hub may be the first to be considered. For candidates within commutable distance, Etsy requires in-office attendance once or twice per week depending on your proximity to the office.

About the ML Enablement Team at Etsy

The ML Enablement initiative owns the systems and infrastructure that support the ML ecosystem end-to-end. Teams within MLE focus on:

• Feature and embeddings infrastructure: Delivering reliable, consistent, high-quality features and embedding data for training and serving ML models.
• Model development and training: Building standardized model development and training workflows that enable fast iteration for ML practitioners.
• Orchestration and integration testing: Streamlining orchestration across our different systems with fast, reliable offline evaluation and model deployment to improve velocity.

This role will flex across these problem spaces depending on business needs, giving you the opportunity to define strategy and deliver impact across multiple high-leverage areas.

Day-to-Day Responsibilities

• Product Strategy: Define the strategy and roadmap for a cohesive ML development experience at Etsy, ensuring consistency across data, training, evaluation, and serving. Use insights from ML product teams, competitive analysis, and advancements in ML to prioritize most impactful investments. Drive semi-annual roadmap planning for your squad, translating it to quarterly objectives and key results.
• Product Execution: Drive operational excellence through biweekly sprint execution, collaborating with engineers to iterate on ML systems to simplify ML workflows and reduce friction in model development and deployment. Work closely with product teams to validate and measure success.
• Product Collaboration: Collaborate with ML product teams to understand their problems and prioritize platform investments that maximize impact.
• Quality Craft: Translate technical opportunities into clear customer outcomes and measurable platform success metrics which translate to business metrics.
• Product Leadership: Represent ML Enablement in cross-org planning with teams in Search, Ads, Recommendations, Growth, and Data Enablement.

Qualities That Will Help You Thrive In This Role

• Technical fluency and 3+ years of product management experience, with at least 1-2 years in ML, data, or infrastructure-focused platform product teams (e.g., model training and inferencing, feature stores, model evaluation, orchestration frameworks).
• Proven track record of working effectively with engineering in defining strategy and driving execution in complex, cross-functional technical spaces where customer empathy is more nuanced (i.e., internal ML practitioners vs. end-users).
• Strong communication and collaboration skills to align stakeholders across engineering, machine learning, and infrastructure teams.
• Comfort navigating ambiguity and change in a dynamic, evolving organizational context.
• Strong bias for action and impact: A proactive demeanor with a passion for creative problem solving. Comfortable navigating ambiguity while maintaining focus on delivering results that matter to buyers and the business.

Key skills/competency

• Machine Learning (ML)
• Product Management
• ML Platform Development
• Developer Experience
• Product Strategy
• Roadmap Planning
• Cross-functional Collaboration
• Feature Stores
• Model Deployment
• MLOps