San Francisco, CA
Onsite
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.
We’re looking for hands-on builders–intellectually curious, deeply technical leaders eager to shape the future of AI and ML at Whatnot. You’ll lead the development and scaling of the core infrastructure that powers machine learning and self-hosted large language model applications across the company, working side by side with machine learning scientists to bring cutting-edge models powered by near-realtime features into production and unlock entirely new product experiences. This means building systems that make advanced ML dependable and fast at scale–from low-latency deep learning model serving and streaming feature ingestion to distributed training and high-throughput GPU inference. This is a role that requires strong technical depth–potential candidates should be excited about getting and staying in the weeds. You will be expected to up-level architectural discussion, provide technical feedback, and code at least a day a week.
Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
Guide the prototyping, deployment, and productionization of novel ML architectures that directly shape user experience and marketplace dynamics.
Help design and scale inference infrastructure capable of serving large models with low latency and high throughput.
Oversee and evolve real-time feature pipelines that feed both our online and offline stores, ensuring single-second feedback from behavioral signals, high reliability, and model training fidelity.
Drive feature platform improvements and expand scope to cover non-ML use cases such as fraud rules where point-in-time backtesting is also critical.
Lead the development of distributed training and inference pipelines leveraging GPUs and both model and data parallelism.
Optimize system performance by managing resource utilization and developing intelligent feature caching strategies.
Empower scientists to iterate faster by building abstractions, APIs, and developer tools that simplify the development of near-realtime features and model iteration.
Roll out ever-better ergonomics around model training and deployment.
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.
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 Tech Lead Manager, ML Platform you should have 1+ years of TLM experience developing production machine learning systems at consumer-scale loads, plus:
Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
5+ years of hands-on 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.
Experience working with with ML-specific tools and frameworks such as MLFlow, LitServe, TorchServe, Triton
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.
Generous Holiday and Time off Policy
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
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
16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
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.
