Machine Learning Engineer

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London, Greater London, England, GBR
In-Office
eCommerce • Mobile
Buy, Sell & Go Live
The Role
🚀 Join the Future of Commerce with Whatnot!

Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.

As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.

We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. 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.

💻 Role

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, productionizing 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.

Key Responsibilities

  • 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.

👋 You

People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.

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 JavaScript) 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 ownership of data and ML pipelines.

  • Analytics & marketplace insight: Strong data analysis skills; capable of deep behavioral analysis to uncover trends and insights within a complex advertising marketplace.

  • Product sense & collaboration: Excellent product instincts—you think first about users and business impact, can translate product needs into measurable ML solutions, and collaborate effectively with product, data science, engineering, and other cross‑functional partners.

  • Teamwork & leadership: A highly collaborative mindset, especially with other senior ML ICs and cross‑functional ML counterparts, to drive measurable business outcomes.

  • Bonus: experience in formal or informal leadership roles (e.g., Technical Lead or Manager) and a track record of raising the bar for engineering excellence.

🎁 Benefits
  • Generous Holiday and Time off Policy

  • Health Insurance options including Medical, Dental, Vision

  • Work From Home Support

    • Home office setup allowance

    • Monthly allowance for cell phone and internet

  • Care benefits

    • Monthly allowance for wellness

    • Annual allowance towards Childcare

    • Lifetime benefit for family planning, such as adoption or fertility expenses

  • Retirement; Pension plans internationally

  • Monthly allowance to dogfood the app

    • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).

  • Parental Leave

    • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

💛 EOE

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

What the Team is Saying

Kaitlyn
Shahana
Logan Bestwick
Charles

Whatnot Compensation & Benefits Highlights

  • Healthcare Strength Healthcare is considered comprehensive with multiple plan options through a major carrier and broad ancillary coverage including dental, vision, life, and disability. Employer cost share is described as very high for employees, supporting strong affordability.
  • Parental & Family Support Paid parental leave with a structured return and additional childcare and family‑planning allowances provide robust support for growing families. These benefits extend beyond standard offerings and are emphasized as core parts of the package.
  • Leave & Time Off Breadth Flexible PTO is paired with company‑wide winter and summer breaks to create predictable recharge windows. This combination offers both autonomy and coordinated downtime across teams.

Whatnot Insights

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The Company
HQ: Culver City, California
1,200 Employees
Year Founded: 2019

What We Do

We bring people together around the things they love and turn their passions into their livelihood.

Why Work With Us

Passion is the centerpiece of our culture. We’ve got passionate buyers, sellers, and employees. We want you to bring your passions to Whatnot.

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Whatnot Offices

Remote Workspace

Employees work remotely.

Our “office optional” policy lets you work where you’re most productive. With options of working from home, in person, or a mix of both. We have office hubs within the US, UK, Ireland, Poland, and Germany today.

Typical time on-site: None
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