Faire

3 weeks 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: 6 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

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

Website LinkedIn

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Faire

3 weeks 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: 6 hours agoStatus: Live

Job Summary

Location: Waterloo, Toronto

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

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Headquarters: San Francisco, United States

Founded: 2017

Website LinkedIn