Machine Learning Engineer

Join the Future of Commerce with Whatnot!

Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re re-defining e-commerce by blending community, shopping, and entertainment into a community just for you. As a remote co-located team, we’re inspired by innovation and anchored in our values. With hubs in the US, UK, Germany, Ireland, Poland, and Australia, we’re building the future of online marketplaces –together.

From fashion, beauty, and electronics to collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone.

And we’re just getting started! As one of the fastest growing marketplaces, we’re looking for bold, forward-thinking problem solvers across all functional areas. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business, and bring people together through commerce.

Ads+Promos is a growing engineering org at Whatnot that is dedicated to building products and systems to help sellers grow their business, stand out in a competitive marketplace and strengthen their brands.

The Ads Quality team is responsible for ensuring the most relevant, high-performing ads and promotions reach users across all our ad formats and discovery experiences. This team owns the retrieval and ranking stages in the ads delivery funnel, balancing relevance for users and ROI for advertisers. As we expand into new features & ad formats, this team will be critical to maintaining user trust while scaling advertising revenue.

We're seeking an experienced Machine Learning Engineer who enjoys developing, product ionizing models and leading technical direction across teams. In addition, as we grow, this role will have opportunities to extend further into leadership & management responsibilities.

This is a high-impact role where you'll work with other Senior ICs to drive the technical direction, mentor exceptional engineers, and work cross-functionally to build the next generation of ads products.

Team members in this role must live within commuting distance of our London, UK hub.

• Lead the design and evolution of machine learning models that power ads retrieval, ranking, and auction systems at scale.

• Own end to end ML systems, including training pipelines, feature infrastructure, and low latency online inference for real time and batch use cases.

• Apply advanced statistical and ML techniques to improve ads relevance, marketplace efficiency, and Seller outcomes.

• Define experimentation strategies, success metrics, and evaluation frameworks, and drive iteration through rigorous offline and online testing.

• Establish model and system observability through metrics, dashboards, and reliability best practices.

• Provide technical leadership through mentorship, design reviews, and raising engineering standards across the Ads+Promos org and Engineering at Whatnot.

• Stay current on advances in machine learning and ads auction systems, and drive adoption where they deliver clear impact.

Beyond strong alignment with Whatnot’s cultural values, you’ll bring:

• Advanced degree and experience: M.S. or Ph.D. in Computer Science, Machine Learning, Economics, Statistics, or equivalent professional experience, plus 8+ years building production software and ML pipelines/systems, including technical leadership (project/tech lead or equivalent).

• Applied ML domain expertise: Experience applying statistical and machine learning methods in at least one of:
  ads, search, recommendations, content understanding, NLP, or large language models.

• Core engineering & ML stack: Strong proficiency in Python and at least one major ML stack (
  scikit‑learn, PyTorch, LightGBM
  , etc.), with solid software engineering fundamentals and backend skills; capable of building scalable systems (our stack primarily includes Python, Elixir, and Java Script ) and deploying ML models to production (batch and/or real‑time).

• Data platform & features:
  
  Experience with
  data orchestration frameworks (e.g.,
  Dagster, Kubeflow
  ) and feature store design
  , including end‑to‑end…