LLM Platform Engineer

About the Position

LLM Platform Engineer

Whatnot is the largest live 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.

Responsibilities

• 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.

Requirements

• Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
• 4+ years of professional experience developing machine learning systems and algorithms.
• 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 PostgreSQL, DynamoDB, Elasticsearch, Redis.
• Firm grasp of visualization tools for monitoring and logging e.g. DataDog, 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.

We Offer

• Compensation: $245,000 - $345,000/year + benefits + stock options.
• Benefits:
  • Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
  • 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; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  • Monthly allowance to dogfood the app
  • 16 weeks of paid parental leave + one month gradual return to work

About the Company

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.