Staff Applied ML / AI Scientist - Search

Faire; Toronto, Kitchener; Hybrid; CAD 196,000 - 270,000; Full time

Job summary

A leading tech company in Ontario is looking for a Staff Applied AI/ML Scientist to drive the development of advanced Search and Recommendation systems. The ideal candidate will have over 7 years of experience in large-scale ML systems, expertise in deep learning libraries like PyTorch, and a strong capability in personalization techniques. This role involves mentoring a team, fostering an innovative work environment, and is essential for ensuring high-quality customer experiences.

Benefits

Equity options

Comprehensive benefits

Flexible remote work options

Qualifications

• 7+ years of experience building large-scale ML systems.
• Hands-on experience with deep learning libraries and vector search infrastructure.
• A strong track record of productionizing models using LLMs.

Responsibilities

• Own the next-generation Search engine and design natural language search systems.
• Lead model development and retain GPU-based deployment efforts.
• Integrate LLMs and deep personalization embeddings for product feeds.

Skills

Deep learning libraries (e.g., PyTorch)

Large-scale ML systems

Personalization techniques

Strong Python skills

Cross-functional collaboration

Education

MS or PhD in Computer Science, Statistics, or a related STEM field

Tools

Faiss

ScaNN

Pinecone

Job description

About this role

As a Staff Applied AI / ML Scientist on the Search Group, you’ll drive the technical vision, ML algorithm strategy, and system design powering one of the most critical levers for customer value and company growth—Search (think about what you do when you land on any e-commerce site). You’ll lead the advancement of real-time Search and Recommendation systems behind our next-generation shopping experiences.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products / brands for any given query from the users.

This is a rare opportunity to own end-to-end personalization in a high-scale, deeply multi-modal environment—while mentoring a team of talented scientists and engineers.

What you’ll do

• Own 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
• Design and productionize natural language search and discovery systems, enabling intelligent agents to generate relevant and personalized collections, explain search results, and assist retailers in browsing, filtering, and evaluation.
• Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.

Qualifications

7+ years of experience building large-scale ML systems, including 3+ years in search, recommendation, or ads ranking.

Hands-on experience with deep learning libraries (e.g. PyTorch) and vector search infrastructure (e.g. Faiss, ScaNN, Pinecone).

A strong track record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization.

A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production.

Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments.

Excellent communication and cross-functional influence—you raise the technical bar beyond your immediate team.

Great to Have

Contributions to open-source ML libraries or peer-reviewed publications in ML / AI.

MS or PhD in Computer Science, Statistics, or a related STEM field.

Salary Range

Canada : the pay range for this role is $196,000 CAD to $269,500 CAD per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Effective January 2025, Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays. 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.

Applications for this position will be accepted for a minimum of 30 days from the posting date.

Why you’ll love working at Faire

We are entrepreneurs : Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process.

We are using technology and data to level the playing field : We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.

We build products our customers love : Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.

We are curious and resourceful : Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.

Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our (https : / / bit.ly / faire-form)