Senior Applied AI/ML Scientist

About the role

You will serve as the technical and science lead for Compass, an agentic AI assistant designed to help retailers make informed purchasing decisions. This role is an individual contributor position focused on owning the end-to-end delivery of product features from conception to production. You will define the technical strategy and quality standards that govern how agents behave, interact, and improve over time. The position requires fluency in both system architecture and applied machine learning to solve real-world retail problems. You will work closely with engineers and product partners to turn high-level objectives into robust, scalable solutions. Success in this role depends on your ability to bridge the gap between research ideas and shipping reliable user-facing features. You will be responsible for ensuring that agentic workflows are measurable, maintainable, and aligned with business outcomes.

Key facts

What you'll do

• Define the technical direction for agentic products, including tool-calling strategies, context management, and quality measurement.
• Build and ship features across the full stack, including the FLARE Python application, data pipelines, and frontend surfaces.
• Convert ambiguous product goals into structured, tactical development plans that balance ambition with technical constraints.
• Establish standards for eval-driven development, including offline suites and LLM-as-judge metrics to guide improvements.
• Partner with engineering teams to manage architectural tradeoffs, ensuring that systems remain reliable and performant at scale.
• Provide technical mentorship to peers through code reviews, prototyping sessions, and the creation of clear design documentation.
• Design experiments to evaluate agent behavior, analyze failure modes, and iterate on prompts, tools, and guardrails.
• Collaborate with data teams to curate high-quality training and evaluation datasets that reflect real-world retail workflows.
• Advocate for best practices in reproducibility, monitoring, and testing for AI-powered features in production environments.
• Identify opportunities to simplify complex workflows while preserving the expressive power needed for advanced agentic behaviors.
• Lead the design of context management systems that balance memory, latency, and correctness for multi-turn interactions.
• Define and track product-specific KPIs that capture both user satisfaction and operational efficiency of agentic features.
• Work with product managers to translate business requirements into technical specifications that engineering teams can execute against.
• Ensure that all implemented solutions adhere to safety and compliance standards relevant to e-commerce and customer-facing applications.

Requirements

• 5+ years of industry experience developing and deploying production ML/AI systems with measurable impact on business outcomes.
• Hands-on experience shipping LLM-powered or agentic features in a core product where reliability and performance are critical.
• Strong foundation in applied ML, including experimental design, data strategy, and rigorous evaluation methodologies.
• Demonstrated ability to ship code across backend, data, and frontend layers in a fast-paced product environment.
• Proficiency in AI-native development workflows and modern coding tools that support rapid iteration and debugging.
• Ability to design systems that are simple to maintain, debug, and extend while remaining scalable for future growth.
• Comfort working with ambiguous requirements and turning them into well-defined technical milestones and acceptance criteria.
• Excellent written and verbal communication skills to articulate technical concepts to both technical and non-technical stakeholders.

Nice to have

• Background in two-sided marketplaces or e-commerce where matching decisions directly impact business metrics.
• Experience transitioning read-only assistants into action-taking agents with carefully designed safety guardrails.
• Practical knowledge of OpenAI Agents SDK or similar frameworks that simplify agent orchestration and tool use.
• Familiarity with hybrid context strategies, Snowflake-backed grounding, or preload-over-RAG methods to improve reliability and speed.
• Experience with 0 to 1 product development, where you shaped the vision, architecture, and execution strategy from scratch.
• Expertise in retrieval, recommendation, or personalization modeling and how these systems integrate with agent workflows.
• Public record of technical writing, such as blogs or documentation, or open-source contributions related to applied AI systems.

Practical notes

• Hybrid work policy: 3 days per week in-office on Tuesdays, Thursdays, and one flex day agreed with the team.
• Employees may work remotely for up to 4 weeks per year for locations outside the primary work region.
• Faire utilizes AI tools as part of the applicant screening process to evaluate technical qualifications and role fit.
• Reasonable accommodations are available for candidates with disabilities during the recruitment process to ensure fair evaluation.
• Applicants are encouraged to highlight relevant experience in agentic systems, data-driven product development, and cross-functional collaboration.
• The selection process may include technical assessments, take-home exercises, and interviews focused on real-world scenarios.
• This role reports to the technical leadership of the Compass product area within the Discovery pillar.
• The successful candidate is expected to contribute to internal knowledge sharing and help elevate the overall AI/ML practices across the organization.
• All employment decisions are made in compliance with applicable laws and Faire's commitment to diversity and inclusion.
• Final compensation details, including equity grants and specific benefit selections, will be discussed during the offer stage.
• Candidates should be prepared to discuss concrete examples from their previous work that demonstrate agentic system design and measurable impact.
• The position may involve occasional travel to office locations for planning sessions, though the majority of work can be performed remotely.
• This role is full-time and based in Canada, with standard employment benefits and professional development opportunities available.