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Whatnot
Software Engineer Recommendation Systems
atĀ Whatnot
21 days ago | 63 views | 1 applications

Software Engineer Recommendation Systems

Full-time
San Francisco
Per year
$128,000 To $145,000

About the company

Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. Weā€™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. Weā€™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:

šŸ“Ship product features to deliver high-quality Discovery experiences for users šŸ“Build and maintain a scalable, stable, low latency feed and browse experience šŸ“Build the services and infrastructure to enable advanced recommendation systems solutions for real-time, dynamic feeds šŸ“Partner closely across the machine learning, platform, and product engineering teams to utilize models to solve discovery problems šŸ“Contribute scalable solutions across various serving stacks at the feed, search, machine learning service, and Discovery application layers. šŸ“Define and advance our technical approach to scalable recommendation systems.

You

šŸ“Curious about who thrives at Whatnot? Weā€™ve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here. šŸ“As our next Software Engineer you should have 5+ years of experience, plus: šŸ“Bachelorā€™s degree in Computer Science, Statistics, Mathematics, Software Engineering, a related technical field, or equivalent work experience. šŸ“Industry experience with a track record of applying practical methods to solve real-world problems on consumer scale data. šŸ“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. šŸ“Experience in machine learning fields (e.g. Recommendations, Content Understanding and Search). šŸ“Expert at designing and building scalable and maintainable backend systems. šŸ“Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana šŸ“Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Kafka, Flink/Spark.

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