- Experience
- 5+ yrs
- Salary
- CAD 180,000 – CAD 247,500 / year
- Openings
- 1
- Posted
- 4 weeks ago
- Work mode
- Work from home
- Resume
- Required to apply
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Job description
Company Overview
Faire is a technology-driven wholesale platform dedicated to empowering local businesses. Connecting independent retailers globally, Faire leverages data, machine learning, and innovative technology to transform a traditionally fragmented wholesale marketplace. The platform helps local shops discover unique products worldwide, fostering growth and thriving communities.
About the Role
We are seeking a Senior Applied AI/ML Scientist to lead the science and technical direction of Compass — our AI-powered retailer assistant integrated within our Discovery Pillar. This role focuses on enhancing agent quality through data analysis, evaluation, and model development, while rapidly delivering end-to-end product features. As a hands-on contributor, you will guide data-driven strategies and build products across AI, machine learning, and backend systems, shaping the future of the retailer assistant.
Key Responsibilities
- Lead scientific and technical vision for Compass's agentic AI products, strategizing how Faire’s proprietary data, agent mechanisms, and context management (preload vs. tool-calling vs. hybrids) empower the assistant.
- Develop and launch retailer assistant features across Python applications, data infrastructure, tool integrations, and user interfaces, leveraging AI workflows to maximize efficiency.
- Convert ambiguous product initiatives into clear, phased plans focusing on impactful, low-risk developments.
- Establish robust evaluation and experimentation frameworks to assess agent quality using offline tests, language model judgment metrics, and journey-centric benchmarks.
- Make pragmatic engineering design decisions balancing immediate delivery with future scalability and maintainability.
- Collaborate with engineering teams on system architecture and deployment, serving as the scientific liaison to related groups such as Search, Personalization, and Platform teams.
- Enhance team expertise through prototype reviews, data analysis, design critiques, and paired programming.
Required Qualifications
- Over five years of professional experience designing and deploying machine learning and AI systems with significant business outcomes, including hands-on involvement in data, evaluation, modeling, and quality assurance.
- Proven experience shipping features powered by agentic AI or large language models in production, with strong understanding of agent design trade-offs including evaluation tactics, latency, costs, reliability, and failure management.
- Robust applied machine learning and data science skills with capability to reason from data, design experiments, and leverage structured or proprietary datasets to enhance product functionality.
- Demonstrated ability to move quickly and deliver quality results across multiple technology stacks including backend, data systems, and preferably frontend.
- Proficiency in AI-native workflows, employing AI coding tools and agent frameworks to significantly increase productivity.
- Strong architectural insight, capable of designing systems that are simple now yet scalable without rework as demands grow.
- Highly autonomous, resourceful, and exhibits sound judgment about when to escalate versus independently resolve challenges.
- Fluency in engineering principles sufficient to make informed architectural decisions.
Preferred Qualifications
- Experience in e-commerce, marketplaces, or two-sided platforms understanding retailer and brand dynamics.
- Background in advancing assistants from read-only roles to safe, actionable agents incorporating confirmation patterns and containment strategies.
- Practical experience with OpenAI Agents SDK or similar agentic AI frameworks in live environments.
- Familiarity with context strategies such as preload-over-RAG, Snowflake data grounding, or hybrid models.
- Prior involvement in early-stage, zero-to-one product development.
- Expertise in recommendation, retrieval, or personalization modeling techniques.
- Contributions to public discourse through articles, open source projects, or presentations on agentic or applied AI topics.
Compensation and Benefits
The salary range for this position in Canada is from 180000 to 247500 CAD annually. Additional equity and comprehensive benefits are also available. Compensation is based on skills, experience, market factors, and work location and may be revised over time.
Additional Information
The company uses AI-driven processes for candidate screening. Hybrid employees in eligible roles work onsite three days weekly with flexibility for remote work periodically. Reasonable accommodations are provided for applicants with disabilities throughout recruitment and employment.
Why Join Us
- Work on impactful problems affecting customers worldwide with autonomy and direct visibility to results.
- Utilize cutting-edge AI and enterprise technology to maximize daily efficiency.
- Collaborate with skilled, supportive, and growth-oriented colleagues.
- Enjoy competitive pay, equity ownership, and benefits supporting your personal and professional life.
- Be part of an inclusive workplace ensuring equal opportunity and growth for all employees.