Senior Applied AI/ML Scientist - Compass

About Faire

Faire is a technology-driven wholesale platform aimed at revitalizing the local retail ecosystem. Independent retailers worldwide represent a massive and traditionally fragmented wholesale market. Faire leverages advanced technology, data analytics, and machine learning to connect these entrepreneurs, helping local boutiques discover and stock outstanding products globally. Our goal is to empower small businesses by providing them with the tools and insights needed to thrive within their communities.

Role Overview

We are seeking a Senior Applied AI/ML Scientist to join the Compass team, central to Faire’s Discovery Pillar. Compass is an AI-powered assistant designed to help retailers make more informed purchasing decisions by integrating Faire’s proprietary data with agentic AI and web search capabilities. This role demands leading the scientific and technical direction of this product by enhancing agent performance through data, evaluation, and modeling while rapidly delivering end-to-end product features. As a hands-on contributor, you will engage deeply in coding across AI, ML, and backend stacks, transforming ideas swiftly into tangible features.

Key Responsibilities

• Lead the scientific and technical vision for Compass's AI agent-based products, optimizing how proprietary data, agent tools, and contextual information are utilized to improve agent quality and effectiveness.
• Develop and launch retailer assistant functionalities across the Python-based FLARE application, associated data infrastructure, tool integrations, and user interfaces.
• Break down ambiguous strategic objectives into prioritized, risk-managed tactical plans for feature delivery.
• Establish and maintain rigorous evaluation and experimentation frameworks to measure agent quality, including offline tests, LLM-based assessments, and journey-specific quality metrics.
• Make thoughtful engineering decisions balancing simplicity for immediate deployment with scalability for future growth.
• Collaborate closely with engineering teams on system architecture and operational trade-offs and serve as the scientific liaison with related teams including Search, Personalization, and Platform/FLARE.
• Enhance team capabilities through demonstrations, analysis, design reviews, and pair programming.

Candidate Qualifications

• Minimum of five years in industry developing and launching machine learning or AI solutions that demonstrate definitive business value, with direct responsibility for applied science aspects such as data handling, evaluations, and modeling.
• Proven experience delivering agentic or large language model-driven features within production environments, with a nuanced understanding of design considerations including evaluation methods, balancing latency and cost against quality, tool invocation versus context preloading, and safeguarding measures.
• Strong foundation in applied machine learning and data science, capable of designing experiments and evaluations while leveraging proprietary or structured datasets to power product features.
• Demonstrated ability to iteratively ship high-quality software across multiple layers of the technology stack, including backend, data pipelines, and ideally frontend development, reflecting broad technical versatility.
• Proficient in AI-native development workflows, utilizing AI-driven coding tools and agent methodologies to enhance productivity.
• Technically mature with a strategic viewpoint on system architecture that supports both immediate needs and future scalability without extensive rework.
• Highly autonomous and resourceful, exercising sound judgment regarding escalation and resolution of technical challenges.
• Strong engineering fluency enabling informed architectural decision-making.

Preferred Additional Experience

• Background in e-commerce, marketplace platforms, or two-sided retail/brand environments.
• Experience advancing read-only assistant technology towards agent systems capable of safe autonomous actions, including the design of confirmation patterns, operational guardrails, and failure management.
• Hands-on use of OpenAI Agents SDK or comparable agentic frameworks in live production.
• Familiarity with state-of-the-art context strategies such as preload-over-RAG, Snowflake-based data grounding, or hybrid architectures.
• Track record of building products from inception (0 to 1) at early-stage startups or teams.
• Expertise in recommendation, retrieval, or personalization modeling techniques.
• Contributions to public AI research, open-source projects, or presentations that highlight structured insights on agentic or applied AI systems.

Salary and Benefits

This position offers a competitive annual salary range of 180000 to 247500 Canadian dollars. Additional compensation includes equity options and benefits. Actual salary depends on skills, experience, market factors, and primary work location and may be subject to adjustment.

Additional Information

The role is fully remote, with hybrid employees expected onsite three days a week. Hybrid roles permit up to four weeks per year of remote work. Some roles may require full onsite presence.

Faire is committed to equal employment opportunity and provides reasonable accommodations for individuals with disabilities throughout the recruitment process.