- Whatnot
- San Francisco, CA
- Full-Time
- 4 days ago
Machine Learning Platform Engineer.
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Machine Learning Platform Engineer: our view in 3 lines...
- The Role:This role is for an engineer building machine learning platform infrastructure for large-scale model serving and training.
- The Person:The person will own infrastructure for AI and ML models, build low-latency inference systems, and develop distributed training and inference pipelines using GPUs and model and data parallelism.
- Requirements:The ideal candidate has 4+ years of professional experience developing machine learning systems and algorithms, 3+ years of software engineering experience, 1+ years of professional experience developing software in Python, and experience with PostgreSQL, DynamoDB, Elasticsearch, Redis, DataDog, Grafana, AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, and Flink.
About the role
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 <u>values</u> 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 <u>fastest growing marketplaces</u> and were recently named the <u>#1 Best Startup Employer in America</u> by Forbes. Check out the latest Whatnot updates on our <u>news</u> and <u>engineering blogs</u> 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 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:
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Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
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Prototype, deploy, and productionalize novel ML architectures that directly shape user experience and marketplace dynamics.
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Design and scale inference infrastructure capable of serving large models with low latency and high throughput.
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Build distributed training and inference pipelines leveraging GPUs and both model and data parallelism.
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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:
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Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
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3+ years of software engineering experience building and maintaining production systems for consumer-scale loads.
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1+ years of professional experience developing software in Python
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Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams.
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Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis.
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Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana.
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Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink.
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Professionalism around collaborating in a remote working environment and well tested, reproducible work.
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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
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Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
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Health Insurance options including Medical, Dental, Vision
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Work From Home Support
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Care benefits
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Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
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Monthly allowance to dogfood the app
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Parental Leave
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.
$245K – $345K
The salary or hourly rate range may be inclusive of several levels that would be applicable to the position. Final salary or hourly rate will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary or hourly rate, not benefits or equity.
Whatnot is a community marketplace where you can safely buy, sell, go live and build a community with other like-minded people.
We got our start offering a buying and selling experience to collectors of Funko Pops and Pokemon cards. We became the leading marketplace for those communities and have found success launching into categories like sports cards, NFTs, and vintage fashion.
In July of 2022, we raised $260 million in a Series D funding round bringing our valuation to $3.7 billion, a 2.5x increase since our $1.5 billion valuation in September of 2021.
Our mission is to enable anyone to turn their passion into a business and bring people together through commerce. We enable anyone to connect, transact and build a business in one place -- Whatnot is bringing the in-person retail experience online.
