Software Engineer – Search and Discovery
| Company | WhatNot |
|---|---|
| Location | Seattle, WA, USA, San Francisco, CA, USA, Los Angeles, CA, USA, New York, NY, USA |
| Salary | $215000 – $245000 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- 5+ years of 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
- 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)
- 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.
Preferred Qualifications
- Deep experience with several of the following: Industry experience in building and scaling a platform to handle high volume / throughput applications
- 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)