Job description

🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest live 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. 💻 Role We're looking for entrepreneurial software engineers who thrive on ambiguous, 0-to-1 work. You’ll design and deploy both traditional ML models and infrastructure (contextual bandits to manage ad spend, shipment ETA predictions) and LLM-powered systems (RAG pipelines, human-in-the-loop evaluation frameworks) to address the business’s most pressing problems. Your job will change every ~12 months as we hand off stable products and pivot to address the business’s next big need. Strong applicants display exceptional business judgement and are equally comfortable contributing to production infrastructure and training the models that run on it. They build for the long term while finding ways to aggressively pull forward business impact. What you'll do: • Develop and deploy new both production machine learning algorithms and core infrastructure to enrich the buyer and seller experience. • Contribute to and set direction across the entire machine learning development process: opportunity sizing, feature engineering, model training, evaluation, load testing, deployment, and alerting. • Design and implement supporting software infrastructure to unblock your work: streaming pipelines, async worker queues, event enrichment infrastructure, continuous training loops, model monitoring systems, LLM tool access controls, and dynamic agent evaluation framework to give just a few examples • Define project roadmaps that deliver value quickly while building towards scalable, extensible long-term systems • Bridge research and production: take an experimental idea and harden it into a scalable, well-tested, monitored system. • Communicate tradeoffs and findings clearly to product and leadership. 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 Seattle or San Francisco hub. 👋 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 Software Engineer, Core Machine Learning you should have 4+ years of professional experience, plus: • Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent work experience. • 2+ years of software engineering experience building and maintaining production systems at consumer scale. • 2+ years of hands-on experience training and deploying traditional ML models in production (e.g. classification, ranking, or regression models using PyTorch, LightGBM, or scikit-learn) • 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 Kubernetes, 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: $180,000 - $300,000/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 • 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. Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam. 💛 EOE 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.

Requirements

Must-haves

Join the Future of Commerce with Whatnot!
Develop and deploy new both production machine learning algorithms and core infrastructure to enrich the buyer and seller experience.
Contribute to and set direction across the entire machine learning development process: opportunity sizing, feature engineering, model training, evaluation, load testing, deployment, and alerting.
Define project roadmaps that deliver value quickly while building towards scalable, extensible long-term systems
Bridge research and production: take an experimental idea and harden it into a scalable, well-tested, monitored system.
Communicate tradeoffs and findings clearly to product and leadership.
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 Software Engineer, Core Machine Learning you should have 4+ years of professional experience, plus:
Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent work experience.
2+ years of software engineering experience building and maintaining production systems at consumer scale.
2+ years of hands-on experience training and deploying traditional ML models in production (e.g. classification, ranking, or regression models using PyTorch, LightGBM, or scikit-learn)
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 Kubernetes, 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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlllmmachine learningawskubernetes

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401k

Parental Leave

Wellness