Top Tech Jobs & Startup Jobs

The role involves managing People Team data, ensuring its integrity, establishing governance standards, and collaborating with IT on AI projects. It requires technical skills, AI tool evaluation, and problem-solving abilities while translating needs between departments.

Own the full ML lifecycle for ads bidding stack, developing models for auction optimization and collaborating with a team to enhance platform effectiveness.

As a Senior Data Scientist/Machine Learning Engineer, you will improve product listing quality through ML and AI, collaborating across teams to implement solutions.

The Strategy & Analytics Senior Lead will drive product decisions through analysis, partnering with cross-functional teams to generate insights and enhance operational processes.

Own the technical vision and evolution of Faire's ML platform: design scalable training/inference workflows, set MLOps standards, implement Unity Catalog and Databricks best practices, optimize cost and reliability, integrate LLM workflows, mentor engineers, and lead cross-functional initiatives to accelerate data science velocity.

Lead design and production of next-generation search and personalized recommendation systems using LLMs, dense retrieval, transformers, GNNs, and MLOps. Drive model development, GPU-based deployment, and <100ms low-latency ranking while mentoring applied scientists and MLEs and collaborating cross-functionally to productize search experiences.

Lead a 15-person GTM/RevOps organization to define strategy, forecasting, territory design, and AI-enabled workflows. Own AI roadmap, build and validate automation tools, drive enablement and adoption, measure impact on rep productivity and pipeline, and hire and develop a high-performing team.

Lead retailer product marketing strategy and a team of PMMs to define positioning, messaging, and GTM for complex retailer products. Own retailer narrative, acquisition initiatives like Opening Soon, cross-functional partnership, and research to validate messaging. Measure impact on GMV and retention, and model AI adoption to improve team productivity.

Own product-area positioning and end-to-end GTM strategy. Drive launches, adoption, and cross-functional enablement. Conduct customer research, translate insights into clear messaging, measure impact with data, and use AI tools to accelerate PMM work.

Design, operate, and optimize a scalable ML platform: productionize ML workloads, implement governance (Unity Catalog), build CI/CD with Terraform and GitHub Actions, configure IAM/RBAC, establish observability, and enable data scientists to move models from notebook to production.