Whatnot is looking for a Machine Learning Platform Engineer to design and scale the core infrastructure that powers machine learning and self-hosted large language model applications across the company. You will work side by side with machine learning scientists to bring models into production and unlock new product experiences.
What You'll Do
- Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
- Prototype, deploy, and productionalize novel ML architectures that directly shape user experience and marketplace dynamics.
- Design and scale inference infrastructure capable of serving large models with low latency and high throughput.
- Build distributed training and inference pipelines leveraging GPUs and both model and data parallelism.
- Stretch beyond your comfort zone to take on new technical challenges as we scale AI across Whatnot’s ecosystem.
What We're Looking For
- 4+ years of professional experience developing machine learning systems and algorithms.
- 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.
Technical Stack
- Languages: Python
- Databases: PostgreSQL, DynamoDB, Elasticsearch, Redis
- Monitoring: DataDog, Grafana
- Cloud & Infrastructure: AWS Sagemaker, AWS Lambda, AWS Kinesis, AWS S3, AWS EC2, AWS EKS/ECS, Apache Kafka, Flink
Benefits & Compensation
- Compensation: $245,000 - $345,000/year + equity: stock options.
- 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.
- Parental Leave: 16 weeks of paid parental leave + one month gradual return to work.
Work Mode
This is a hybrid position available in New York, Seattle, Los Angeles, and San Francisco.
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.
