Slickdeals

Slickdeals

Sr. ML Infrastructure Engineer II, Personalization

San Mateo, CA · Senior

Work authorization required$170k-$220kDetected 65 days ago
SQLElasticsearchVector DatabasesAWSCloud PlatformsDockerKubernetesAnsibleLinuxRESTKafkaMachine LearningDeep LearningTensorFlowPyTorchSparkData ScienceLLMsMLOpsA/B TestingProblem Solving

About the role

  • About Slickdeals: We believe shopping should feel like winning.
  • That's why 10 million people come to Slickdeals to swap tips, upvote the best finds, and share the thrill of a great deal.
  • We're profitable, passionate, and in the middle of an exciting evolution-transforming from the internet's most trusted deal forum into the go-to daily shopping destination.

Responsibilities

  • Design, train, and ship recommendation models including two-tower / dual-encoder retrieval, neural ranking, and re-ranking models
  • Build embedding pipelines for users, deals, merchants, and content
  • Define and run rigorous offline evaluation (recall@k, NDCG, MAP, calibration) and partner with data science to design online A/B tests
  • Partner with product and data science on personalization surfaces - homepage, feeds, deal pages, search re-ranking, and lifecycle channels
  • Build and own end-to-end ML pipelines for recommendations: data preparation, training, evaluation, deployment, and monitoring
  • Design and operate low-latency model serving for high-QPS recommendation traffic
  • Build feature pipelines and feature-store patterns that maintain online/offline parity
  • Design, architect, and build reliability, observability, and utilization infrastructure for the recommendations stack
  • Improve training cost, turnaround time, and reproducibility on the ML platform; collaborate with data scientists to unblock experimentation
  • Encourage change, especially in support of ML engineering best practices, and maintain a high standard of excellence

Requirements

  • 8+ years of relevant professional experience
  • Demonstrated experience designing, training, and shipping recommendation systems in production - not just classifiers or general ML
  • Proficiency with ML modeling frameworks (PyTorch and/or TensorFlow) (5+ yrs)
  • Experience with model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton, or comparable custom serving infrastructure)
  • Experience with vector retrieval / ANN at scale (e.g., FAISS, ScaNN, OpenSearch k-NN, Pinecone, Weaviate, or similar)
  • Experience working with cloud data processing technologies such as Apache Spark, Elasticsearch, Presto, SQL (3+ yrs)
  • Proficiency in at least two of: Linux, Ansible, Docker, Kubernetes (5+ yrs)
  • Experience in distributed computing (7+ yrs)
  • Experience working with AWS or similar cloud infrastructure (5+ yrs)
  • Experience with hardware / resource management for ML training and/or deployment

Nice to have

  • Experience with feature stores (Feast, Tecton, or custom)
  • Experience with real-time / streaming feature engineering
  • E-commerce, content, or marketplace recommendation domain experience
  • The expected base pay for this role is between $170,000 - $220,000.
  • 401K matching above the industry standard

Compensation

  • Slickdeals Compensation, Benefits, Perks:

Benefits

  • Competitive base salary, annual bonus, and equity package
  • Competitive paid time off in addition to holiday time off
  • A variety of healthcare insurance plans to give you the best care for your needs
  • Professional Development Reimbursement Program
  • iterate on representation learning approaches

Company info

  • We may access publicly available information as part of your application.

Visa & Work Authorization

  • Work Authorization

This listing is sourced directly from Slickdeals's careers page and normalized into a canonical job model.