Machine Learning Platform Engineer

Whatnot
San Francisco, New York, Los Angeles, Seattle
Full timeUSD 245,000 - 345,000 annuallyFunction: DevOps, Cloud & InfrastructureExperience: 4+ yearsEducation: bachelorsSkills: ["Communication","Documentation","Autonomy","Collaboration","Initiative"]

Design and scale the core infrastructure behind machine learning and self-hosted large language model applications. Own production systems powering recommendations, trust and safety, fraud, and seller tooling, from low-latency model serving to distributed training and high-throughput GPU inference. Work with machine learning scientists to productionalize novel architectures, build monitoring and logging for reliable operations, and collaborate in a remote, US-hub commuting environment.

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FursaFursa
Whatnot
Whatnot
2 months ago

Machine Learning Platform Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 59 minutes agoStatus: Live

Job Summary

Design and scale the core infrastructure behind machine learning and self-hosted large language model applications. Own production systems powering recommendations, trust and safety, fraud, and seller tooling, from low-latency model serving to distributed training and high-throughput GPU inference. Work with machine learning scientists to productionalize novel architectures, build monitoring and logging for reliable operations, and collaborate in a remote, US-hub commuting environment.
Location: San Francisco, New York, Los Angeles, Seattle
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Own infrastructure powering AI and ML models across key business surfaces including recommendations, trust and safety, fraud, and seller tooling.
  • •Prototype, deploy, and productionalize novel ML architectures that shape user experience and marketplace dynamics.
  • •Design and scale inference infrastructure for large models with low latency and high throughput.
  • •Build distributed training and inference pipelines using GPUs with model and data parallelism.
  • •Collaborate with machine learning scientists to bring cutting-edge models into production and solve new scaling challenges.

Pay and Benefits

Salary: USD 245,000 - 345,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionRemote WorkHome Office401kPensionParental LeaveChildcare

Key Requirements

  • •4+ years developing machine learning systems and algorithms.
  • •Bachelor’s degree in Computer Science, Statistics, Applied Mathematics (or related) or equivalent experience.
  • •3+ years building and maintaining production systems for consumer-scale loads.
  • •1+ years of professional experience developing software in Python.
  • •Experience with operational/search/key-value databases (PostgreSQL, DynamoDB, Elasticsearch, Redis) and monitoring/logging tools (DataDog, Grafana).
Experience:4+ yearsMachine learningArtificial intelligenceDistributed systems
Education:Bachelor's
Skills:CommunicationDocumentationAutonomyCollaborationInitiative
Tech Stack:PythonPostgreSQLDynamoDBElasticsearchRedisDataDogGrafanaAWS SagemakerLambdaKinesisS3EC2EKSECSApache KafkaFlinkGPUsLLMs

Company Brief

Whatnot
Whatnot is a live-stream shopping marketplace connecting sellers and collectors for trading cards, toys, and collectibles. The platform hosts live auctions and interactive streams, enabling creators and small businesses to sell directly to engaged communities.
Industry: Online Marketplaces
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: United States
Founded: 2019
WebsiteLinkedIn