At Whatnot, we are looking for a Software Engineer, Search and Discovery Platform to be a foundational member shaping our Discovery Platform. You will play a critical role in defining technical direction and designing a world-class, scalable Discovery system for feed, browse, search, and taxonomy systems. This is a highly cross-functional role integrating retrieval, ranking, real-time processing, and content understanding into a highly personalized discovery experience.
What You'll Do
- 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.
What We're Looking For
- 5+ years of software engineering experience.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Software Engineering, a related technical field, or equivalent work experience.
- 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.
- Expert at designing and building scalable and maintainable backend systems.
- Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana.
- Experience managing cloud technologies (AWS or Google Cloud) and comfort with infrastructure-as-code approaches (e.g. Terraform).
- 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.
- Must be within commuting distance of our San Francisco, Los Angeles, Seattle, and New York hubs.
Nice to Have
- Deep experience in machine learning fields (e.g. Recommendations, Content Understanding and Search).
- 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.
Technical Stack
- Python, AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Kafka, Flink/Spark, OpenSearch, ElasticSearch, Lucene, SOLR, DataDog, Grafana, Terraform
Team & Environment
This is a highly cross-functional role, partnering closely with machine learning, platform, and product engineering teams.
Benefits & Compensation
- 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
- Home office setup allowance
- Monthly allowance for cell phone and internet
- Care benefits
- 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
- Parental Leave: 16 weeks of paid parental leave + one month gradual return to work
Work Mode
This is a local-city role, based in San Francisco, CA, Los Angeles, CA, Seattle, WA, or New York, NY.
Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law.
