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

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, 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, 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.