Join Faire as a Staff Applied AI/ML Scientist to lead the development of advanced search and recommendation systems.
Posted by employer 4 months ago
First seen on Joblaze 4 months ago
Last verified on the company career page 13 hours ago
Skills & Technologies
Role intensity
40% coding
AI in the day-to-day
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
Requirements
- Experience
- 7+ years
- Education
- No formal education required
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze summary
In the role of Staff Applied ML/AI Scientist at Faire, the individual will lead the development of advanced search and recommendation systems that enhance user experience on the platform. Key skills include expertise in large-scale machine learning, deep learning frameworks, and natural language processing, with a focus on integrating large language models for personalized product recommendations. This position is ideal for seasoned professionals with over seven years of experience in machine learning, particularly in search or recommendation systems, who are looking to make a significant impact in a fast-paced environment. The role also involves mentoring a team of scientists and engineers,
Joblaze insights
- Listed about 4 months ago — first seen on Joblaze July 3, 2026. Last confirmed on Faire's careers page November 10, 2026.
- This exact title is also open at 2 other locations at Faire: New York City, NY; San Francisco, CA, New York City, NY; San Francisco, CA.
- Starts above 5% of 222 comparable staff ai/ml roles we track (median $230,000 across 58 companies).
Quick facts
- Is the Senior Applied ML/AI Scientist - Search role remote?
- It's hybrid — Faire expects some on-site time in Kitchener-Waterloo, ON; Toronto, ON.
- What's the salary range?
- Faire lists CAD 200,000–CAD 275,000 for this role.
- How much experience is required?
- At least 7 years of relevant experience for this Senior Applied ML/AI Scientist - Search role.
- Where is the role based?
- Faire is hiring for this position in Kitchener-Waterloo, ON; Toronto, ON.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Deep Learning, Graph Neural Networks, Machine Learning, Natural Language Processing, PyTorch, Python.
- What seniority level is this role?
- Faire targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Senior Applied ML/AI Scientist - Search role at Faire.
From the original posting
About Faire
About the role
Search is how retailers do their jobs on Faire. Wholesale queries and retailer expectations look different from consumer e-commerce and the right product depends on the store's category, price point, and aesthetic. When we get it wrong, it costs real money.
The Search algorithms team owns everything between the click on the search bar and the final ranker: typeahead and empty-state suggestions, query understanding, retrieval across five-plus independent sources, relevance modeling, and result-page surfaces like carousels and refinements. Within our scope, scientists own components outright: when you own query understanding here, you own the models, the roadmap, and the metrics.
You'll work across the full modern search stack: transformer-based embedding retrieval serving live traffic, LLMs powering query understanding and query rewriting, fine-tuned vision-language models scoring relevance, and graph-based retrieval — with generative retrieval and semantic IDs on the horizon.
What you'll do
- Contribute to the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with <100ms latency.
- Own one or more search components end to end: problem framing, modeling, production code, experiment design, and the call on what to build next.
- Ship to live traffic and let A/B tests, not opinions, settle what works.
- Raise the team's bar through design reviews, pairing, and honest post-mortems
You're a great fit if you have
- 3+ years building production ML systems, with meaningful time in search, recommendations, or another retrieval-and-relevance domain.
- Shipped models that served real traffic, and owned the experiments that proved (or disproved) their value.
- Depth somewhere in the modern retrieval stack — dual encoders and ANN serving, LLM-based query understanding, learning-to-rank fundamentals — and the ability to pick up the rest.
- Strong Python and the engineering chops to take your own models to production.
- Clear communication with scientists, engineers, and PMs: you make a crisp case for your ideas and update quickly when someone has a better one.
- Excellent product judgment to connect customer and business context to technical decisions
Bonus Points
- Marketplace or e-commerce experience
- Publications, open-source work, or public writing on search and recommender systems.
- MS or PhD in CS, Statistics, or a related field.
Salary Range
Canada: the pay range for this role is $180,000 to $247,500 per year.
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
This job posting is for an existing vacancy.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Standard company text repeated across Faire's postings is omitted here.