Senior Applied ML/AI Scientist - Search

Faire
Waterloo, Toronto, Ontario, New York, San Francisco
Workplace: HybridFull timeCAD 200,000 - 275,000 annuallyFunction: Research & Scientific (R&D)Experience: 7+ yearsSkills: ["Communication","Cross-functional influence","Execution","System reliability","Ownership"]

Drive the technical vision for real-time Search and Recommendation powering next-generation shopping experiences. Lead end-to-end personalization across LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with <100ms latency. Design and productionize natural language search/discovery and mentoring practices for senior Applied Scientists and MLEs, including GPU-based deployment using Triton and MLOps best practices.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Faire
Faire
2 months ago

Senior Applied ML/AI Scientist - Search

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Drive the technical vision for real-time Search and Recommendation powering next-generation shopping experiences. Lead end-to-end personalization across LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with <100ms latency. Design and productionize natural language search/discovery and mentoring practices for senior Applied Scientists and MLEs, including GPU-based deployment using Triton and MLOps best practices.
Location: Waterloo, Toronto, Ontario, New York, San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Sr. Manager level

Key Responsibilities

  • •Own the next-generation Search engine integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning for personalized product feeds with <100ms latency.
  • •Design and productionize natural language search and discovery systems for intelligent agents that generate personalized collections, explain results, and assist retailers with browsing and filtering.
  • •Lead model development and GPU-based deployment using frameworks like Triton to scale inference reliably and efficiently.
  • •Mentor and grow senior Applied Scientists and MLEs; establish best practices for model development, agent workflow evaluation, and MLOps.

Pay and Benefits

Salary: CAD 200,000 - 275,000 annually
Equity and Bonus:Equity

Key Requirements

  • •7+ years building large-scale ML systems, including 3+ years in search, recommendation, or ads ranking.
  • •Hands-on deep learning experience (e.g., PyTorch) and vector search infrastructure (e.g., Faiss, ScaNN, Pinecone).
  • •Track record productionizing models that blend LLMs (e.g., BERT, GPT-class) with structured features for personalization.
  • •Strong Python skills with deep respect for system reliability and ownership in high-stakes environments.
  • •Excellent communication and cross-functional influence; ability to raise the technical bar beyond your immediate team.
Experience:7+ years
Education:
Skills:CommunicationCross-functional influenceExecutionSystem reliabilityOwnership
Tech Stack:PythonPyTorchTritonFaissScaNNPineconeLLMsNatural language processingTransformer-based modelingGraph neural networksDense vector retrievalBERTGPT-classReinforcement learningMLOps

Company Brief

Faire
Operates a wholesale marketplace connecting independent retailers with emerging and established brands, providing ordering, logistics, and payment solutions to help small businesses discover and stock unique products.
Industry: Online Marketplaces
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Headquarters: San Francisco, United States
Founded: 2017
WebsiteLinkedIn