About the company
Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. We’re 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, and Germany today. We’re 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.
Job Summary
What you'll do:
📍Ship product features to deliver high-quality Discovery experiences for users 📍Build and maintain a scalable, stable, low latency feed and browse experience 📍Build the services and infrastructure to enable advanced recommendation systems solutions for real-time, dynamic feeds 📍Partner closely across the machine learning, platform, and product engineering teams to utilize models to solve discovery problems 📍Contribute scalable solutions across various serving stacks at the feed, search, machine learning service, and Discovery application layers. 📍Define and advance our technical approach to scalable recommendation systems.
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 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. 📍Industry experience with a track record of applying practical methods to solve real-world problems on consumer scale data. 📍Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams. You can mentor others and prioritize building inclusive, supportive teams. 📍Experience in machine learning fields (e.g. Recommendations, Content Understanding and Search). 📍Expert at designing and building scalable and maintainable backend systems. 📍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, Kafka, Flink/Spark.
