Top Tech Jobs & Startup Jobs

Own full-cycle recruiting for Product, Design, and Strategy organizations. Partner with executives and hiring managers on talent strategy, sourcing, structured hiring processes, candidate communication, offer negotiation, and onboarding. Maintain applicant tracking data integrity, provide pipeline reporting, champion company values, and support inclusive hiring. The role requires proactive talent pipeline management, strong stakeholder communication, excellent organization, and a focus on candidate experience.

Own the technical direction and roadmap for Faire’s data infrastructure. Build CDC and streaming ingestion from production databases into Kafka, Iceberg, and S3; manage data quality, contracts, observability, SLAs, and reliability. Operate Airflow and Fivetran, lead platform migrations, establish governance, mentor engineers, and collaborate with data scientists, analysts, and senior engineering teams. The role requires hands-on development, architecture leadership, incident ownership, and cross-team influence.

Develop and productionize personalized search ranking, recommendation, and natural-language discovery systems. Apply deep learning, transformer models, graph neural networks, multimodal signals, LLMs, and behavioral data to improve search relevance. Partner cross-functionally on experimentation, model development, agent evaluation, and MLOps. Provide technical guidance through code reviews and best-practice sharing while advancing scalable machine-learning systems for e-commerce discovery.

Own end-to-end applied machine learning projects that improve marketplace quality and trust. Build pricing-integrity, product-matching, entity-resolution, attribute-extraction, ranking, and violation-detection models using structured and unstructured data. Develop human-in-the-loop review systems, prioritize enforcement actions under operational constraints, evaluate LLMs, and analyze experiments measuring retailer trust and marketplace GMV. Partner cross-functionally with product, engineering, analytics, and marketplace operations to ship models and deliver business impact.

Leads analytics strategy for Faire’s Discovery pillar, informing search, recommendations, ads, and marketplace decisions. Builds and manages a high-performing strategy and analytics team, establishes analytical rigor and experimentation standards, owns key metrics and datasets, and develops self-serve data tooling and operating systems. Partners cross-functionally to identify opportunities, improve decision-making, and scale analytics practices across the company.

Partners with the Head of Customer Experience to drive strategic planning, analytics, capacity modeling, workforce management, budgeting, and operational execution. Leads cross-functional support initiatives from scoping through launch, translates financial forecasts into operational targets, manages headcount planning, and builds dashboards to monitor CX performance. Collaborates with Finance, Operations, and vendor teams while presenting recommendations to executive stakeholders.

Own and scale Faire’s global equity programs across plan design, administration, accounting, compliance, employee experience, and multiple jurisdictions. Lead public-company readiness, SEC reporting support, insider trading programs, audit readiness, internal controls, equity lifecycle operations, system integrations, and global regulatory risk management. Partner cross-functionally with Finance, Accounting, Payroll, Legal, People, senior leaders, and external advisors while serving as the escalation point for complex equity matters.

Develop AI and machine learning systems for retailer acquisition, engagement, paid marketing optimization, bidding, targeting, AEO content generation, and personalized landing experiences. The role includes causal inference, experimentation, marketing capital allocation, behavioral insights, and scalable solutions for two-sided marketplace challenges. It requires cross-functional collaboration, independent ML solution design, and strong programming and communication skills.

Own end-to-end applied machine learning projects for catalog and listing quality. Build multimodal deep learning and LLM systems to analyze product images, titles, descriptions, and attributes; improve imagery, ranking, exploration, and product information; and develop evaluation workflows involving human feedback. Partner cross-functionally to ship models, measure business impact, and improve discovery and conversion across Faire’s two-sided marketplace.

Own the strategy, roadmap, metrics, and product development for Faire’s search ranking algorithms. Partner with data science, ML platform, discovery infrastructure, and search teams to identify opportunities, diagnose ranking issues, prioritize technical investments, and improve retailer discovery outcomes. The role requires strong product judgment, analytical direction, technical fluency, and experience managing complex, cross-functional initiatives.