Software Engineer, Core Machine Learning
$205k - $275kWhatnot
Core Machine Learning Engineer 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 Whatnot’s 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 emerge. As our next Software Engineer, Machine Learning you should have 5+ years of experience, plus: Bachelor’s 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 platforms–model serving, feature 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. 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. 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.
- 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.
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