LLM Platform Engineer

Role

We’re looking for builders–intellectually curious, highly entrepreneurial engineers eager to shape the future of AI and ML at Whatnot. You’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.

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.

Qualifications

• 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 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.

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 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

Compensation

For US-based applicants: $245,000 - $345,000/year + benefits + stock options. The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options.