LLM Platform Engineer

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

We're looking for builders-intellectually curious, highly entrepreneurial engineers eager to shape the future of AI and ML 'll design and scale the core infrastructure that powers large language model applications across the company, working side by side with machine learning scientists to bring cutting-edge models into production and unlock entirely new product experiences. This means building systems that make AI dependable and fast at scale-from building retrieval systems to more effectively ground LLM responses in Whatnot's business context to developing scalable LLM evaluation frameworks and human-in-the-loop feedback mechanisms.
What you'll do:

• Own the infrastructure powering LLMs across critical business surfaces- supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
• Create robust and scalable LLM evaluation frameworks to measure model performance, guide iteration, and prevent regression via CI/CD.
• Deploy RAG systems and MCP servers to more effectively ground LLM responses in Whatnot's business context while enforcing rigorous PII controls.
• Design efficient human-in-the-loop feedback pipelines that can be used to inform scalable LLM evaluation
• Bridge the gap between research and production, helping to transform experimental ideas into scalable solutions
• 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.

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.

As our next AI/ML Engineer you should have 4+ years of professional experience developing machine learning systems and algorithms, plus:

• Bachelor's degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
• 3+ years of software engineering experience building and maintaining production systems for consumer-scale loads.
• 1+ years of professional experience developing software in Python
• Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams.
• Experience with operational, search, and key-value databases such as Postgre
  
  SQL, Dynamo
  
  DB, Elasticsearch, Redis.
• Firm grasp of visualization tools for monitoring and logging e.g. Data Dog, Grafana.
• Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink.
• Professionalism around collaborating in a remote working environment and well tested, reproducible work.
• Exceptional documentation and communication skills.

Compensation

For US-based applicants:$245,000 - $345,000/year + benefits + stock options

The salary range…