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The Senior Machine Learning Engineer leads technical direction for ML systems focused on personalization and ranking, overseeing architecture and implementation while mentoring team members.

Own and deepen agency relationships to drive adoption of Fetch ad products. Structure partnership deals, create joint business plans, lead agency education and roadshows, collaborate with sales/product/marketing, track progress via QBRs, and funnel business opportunities to grow revenue and renewals.

Own complex analyses and measurement frameworks for a product or business area. Design experiments and statistical/causal models, define and monitor KPIs, quantify impact, and translate findings into product and business recommendations. Partner cross-functionally, mentor junior analysts, and use tools like Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to scale analytics and ensure reproducibility and strong governance.

Lead and grow a team of ML engineers building production ML systems for Fetch's Ad Platform. Translate product strategy into roadmaps, guide design and implementation of models for ranking, targeting, bidding and forecasting, set metrics and experimentation, enforce architectural and operational standards, manage trade-offs across performance and reliability, and drive cross-functional alignment to improve advertiser and member outcomes.

Own complex sales cycles to acquire and grow strategic brand partnerships, using AI-driven tools for outreach, forecasting, and insights. Drive revenue, craft proposals, manage Salesforce, mentor peers, and collaborate cross-functionally to scale AI-enabled sales playbooks and processes.

Lead and grow a team focused on developer experience and internal platforms to improve engineering productivity. Define strategy, own CI/CD/build pipelines, tooling, local dev environments, observability, and automation. Partner across engineering, infra, security, SRE, product, and data to reduce friction, create golden paths, measure impact with delivery and reliability metrics, and drive adoption of AI-assisted developer workflows.

Lead company-level measurement and causal strategy, define MAU×ARPU metrics and semantic mart, set scientific standards for experimentation and analysis, own strategic models (MMM, elasticity, forecasting), partner with engineering to productionize analytics, and raise org-wide scientific maturity through governance, templates, and upskilling.

Partner with Product, Marketing, Growth, Engineering, and Business teams to analyze user behavior, build dashboards and self-serve reports, support A/B testing and experiment measurement, create user segments and cohorts, monitor KPIs, and communicate actionable insights to stakeholders to improve engagement, conversion, retention, and campaign performance.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Senior Product Designer will lead design efforts for the Fetch app, focusing on user experience and creative direction, while collaborating with various teams to launch features that enhance user engagement and satisfaction.