Software Engineer, Core Machine Learning
San Francisco, CA, Los Angeles, CA, New York City, Phoenix, AZ, Seattle, WA, Denver, CO
Whatnot
š Whatnot
Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. Weāre building the future of ecommerce, bringing together community, shopping and entertainment. We are committed to our values, and as a remote-first team, we operate out of hubs within the US, Canada, UK, Ireland, and Germany today.
Weāre innovating in the fast-paced world of live auctions in categories including sports, fashion, video games, and streetwear. The platform couples rigorous seller vetting with a focus on community to create a welcoming space for buyers and sellers to share their passions with others.
And, weāre growing. Whatnot has been the fastest growing marketplace in the US over the past two years and weāre hiring forward-thinking problem solvers across all functional areas.Ā
š» Role
We are looking for intellectually curious, highly motivated individuals to become foundational members of our Core Machine Learning team. You will help drive the development of Whatnotās machine learning operations and work with machine learning engineers across the company to build scalable design patterns that can be repeatedly used to achieve key business goals. Our ideal candidate has experience in spinning up ML platforms e.g. real-time model serving, approximate nearest neighbor retrieval, high-concurrency and low-latency scaling, feature stores, and model lifecycle monitoring. They are also willing and able to flex into an applied research role to develop models that leverage their own components.
What you'll do:
- Drive the development of the machine learning platform roadmap, staying abreast of emerging business needs that the machine learning platform can help address.
- Enhance our machine learning infrastructure--increase reliability, reduce latency, and continually improve the developer experience.
- Develop scalable machine learning design patterns that make it easy for machine learning scientists and engineers to safely deploy models to production.
- Improve model training, management, and monitoring
- Take a leading role in deploying ML models on business critical surfaces & flows.
- Define and advance our technical approach to scalable machine learning.
- Flex outside your comfort zone to help take on new challenges that emergeĀ
š You
Curious about who thrives at Whatnot? Weāve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.
As our next Software Engineer, Machine Learning you should have 5+ years of experience, plus:
- Bachelorās degree in Computer Science, Statistics, Mathematics, Software Engineering, a related technical field, or equivalent work experience.
- 2+ years of professional experience setting up machine learning platformsāmodel serving, features stores, model registries, training pipelines, etc.
- 1+ years of professional experience developing software in Python
- Software engineering experience with a track record of applying practical methods to solve real-world problems on consumer scale data.
- 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, Spark.
- Professionalism around collaborating in a remote working environment and well tested, reproducible work.
- Exceptional documentation and communication skills.
- Experience in applied statistical and machine learning fields e.g. Recommendations, Search, Fraud & Anomaly Detection, Experimentation and Causal Analysis preferred.
š°Compensation
For US-based applicants: $205,000 - $275,000/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.
š 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
- $1,000 home office setup allowance
- $150 monthly allowance for cell phone and internet
- Care benefits
- $450 monthly allowance on food
- $500 monthly allowance for wellness
- $5,000 annual allowance towards Childcare
- $20,000 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
- 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.
š 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.
Tags: AWS Computer Science DynamoDB EC2 E-commerce ECS Elasticsearch Engineering Flink Grafana Kafka Kinesis Lambda Machine Learning Mathematics ML infrastructure ML models Model training Pipelines PostgreSQL Python Research SageMaker Spark Statistics
Perks/benefits: 401(k) matching Career development Cell phone stipend Equity Fertility benefits Flex hours Flex vacation Health care Home office stipend Insurance Medical leave Parental leave Startup environment Wellness
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