Software Engineer, Search & Discovery Platform
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Requirements
• Learn more about the Discovery systems at Whatnot from our blog posts on Whatamix, LLMs for Search. • Industry experience in building and scaling a platform to handle high volume / throughput applications • 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, OpenSearch, ElasticSearch, Lucene, SOLR. • Experience with concurrent programming patterns across distributed systems (AsyncIO python preferred), and optimizations / profiling / observability associated with them. • Experience managing cloud technologies (AWS or Google Cloud) and comfort with infrastructure-as-code approaches (e.g. Terraform). • In addition to these role-specific qualifications, all engineering team members are expected to have: • Proficiency in at least one server-side programming language (preferably Python), common algorithms and data structures, and software design principles. • Self-starter ethic, thriving under a high level of autonomy. • Exceptional interpersonal and communication skills.
Responsibilities
• Build the services and infrastructure to enable advanced recommendation systems solutions for real-time, dynamic feeds • Build a scalable, stable, low latency discovery experience • 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. • We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Seattle, New York City, San Francisco, or Los Angeles hub. • Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.
Benefits
• Generous Holiday and Time off Policy • Health Insurance options including Medical, Dental, Vision • Work From Home Support • Monthly allowance for cell phone and internet • Monthly allowance for wellness • Annual allowance towards Childcare • 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 • Monthly allowance to dogfood the app • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
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