Tech Lead Manager, ML Platform

🚀 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.

We’re looking for hands‑on builders–intellectually curious, deeply technical leaders eager to shape the future of AI and ML ’ll lead the development and scaling of the core infrastructure that powers machine learning and self‑hosted large language model applications across the company, working side by side with machine learning scientists to bring cutting‑edge models powered by near‑realtime features into production and unlock entirely new product experiences.

This means building systems that make advanced ML dependable and fast at scale–from low‑latency deep learning model serving and streaming feature ingestion to distributed training and high‑throughput GPU inference. This is a role that requires strong technical depth–potential candidates should be excited about getting and staying in the weeds. You will be expected to up‑level architectural discussion, provide technical feedback, and code at least a day a week.

• Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.

• Guide the prototyping, deployment, and productionization of novel ML architectures that directly shape user experience and marketplace dynamics.

• Help design and scale inference infrastructure capable of serving large models with low latency and high throughput.

• Oversee and evolve real‑time feature pipelines that feed both our online and offline stores, ensuring single‑second feedback from behavioral signals, high reliability, and model training fidelity.

• Drive feature platform improvements and expand scope to cover non‑ML use cases such as fraud rules where point‑in‑time backtesting is also critical.

• Lead the development of distributed training and inference pipelines leveraging GPUs and both model and data parallelism.

• Optimize system performance by managing resource utilization and developing intelligent feature caching strategies.

• Empower scientists to iterate faster by building abstractions, APIs, and developer tools that simplify the development of near‑realtime features and model iteration.

• Roll out ever‑better ergonomics around model training and deployment.

• Stretch beyond your comfort zone to take on new technical challenges as we scale AI across Whatnot’s ecosystem.

US Based:
We offer flexibility to work from home or from one of our global office hubs, and we value in‑person time for planning, problem‑solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.

Curious about who thrives at Whatnot? We’ve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.

As our next Tech Lead Manager, ML Platform you should have 1+ years of TLM experience developing production machine learning systems at consumer‑scale loads, plus:

• Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.

• 5+ years of hands‑on software engineering experience building and maintaining production systems for consumer‑scale loads.

• 1+ years of…