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 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 into production and unlock entirely new product experiences. This means building systems that make advanced ML dependable and fast at scale-from low-latency, large model serving to distributed training & high-throughput GPU inference.

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.

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.

You

Curious about who thrives at Whatnot? We've found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.

As our next AI/ML Platform Engineer you should have 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.

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.

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
  
  • 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.