Whatnot
Machine Learning Platform Engineer
$210K–$345K
San Francisco, CA +3 · Full-time · Posted Jul 9, 2026
- Location
- San Francisco, CA
New York, NY
Los Angeles, CA
Seattle, WA - Experience
- 7+ years developing machine learning systems and algorithms; 3+ years building and maintaining production systems for consumer-scale loads; 1+ years developing software in Python.
- Education
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent work experience.
About the job
Build and scale machine learning platform infrastructure, including low-latency model serving, GPU inference, and distributed training, to support Whatnot products.
What you'll do
- Own infrastructure for AI and ML models across business areas including recommendations, trust and safety, fraud, and seller tooling.
- Prototype and productionize ML architectures and build scalable, low-latency inference infrastructure.
- Build distributed training and inference pipelines using GPUs and model and data parallelism.
What they ask for
- 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.
- Experience with operational, search, and key-value databases; monitoring and logging tools; and cloud computing platforms and managed services.
Pay
$245,000 - $345,000/year USD base salary; $210K - $300K USD (pay type not specified)
Tools
Python, PostgreSQL, DynamoDB, Elasticsearch, Redis, DataDog, Grafana, AWS Sagemaker
AI focus
Develop and productionize ML architectures and self-hosted large language model applications, including distributed training and high-throughput GPU inference.
Model-written summary · the original posting is authoritative