Staff Machine Learning Engineer - Ad Platform

Fetch is building personalized consumer experiences through machine learning systems focused on personalization, relevance, and ranking. The Staff Machine Learning Engineer will lead the technical direction and execution of an ML team, owning architecture and hands-on development of reliable, scalable models and infrastructure in partnership with product and cross-functional stakeholders.

Responsibilities:

• Serve as the technical lead for a single ML-focused team, setting direction and raising the bar on engineering quality and system design
• Design, build, and scale ML systems supporting personalization, ranking, search, or ad-related use cases
• Own end-to-end architecture for your team’s services, including model training, evaluation, deployment, and serving
• Drive clarity in ambiguous problem spaces, translating product needs into scalable technical solutions
• Lead design reviews and ensure thoughtful tradeoffs around latency, reliability, experimentation, and maintainability
• Partner closely with product, data, and engineering stakeholders to deliver measurable business impact
• Mentor engineers through hands-on technical guidance, feedback, and example
• Use AI tools to accelerate development and improve system design, including:
• Prototyping and validating ideas with LLM tools
• Leveraging AI for code iteration and experimentation
• Using AI assistants for architecture diagramming and design validation
• Exploring LLM-powered features where appropriate

Requirements:

• 12+ years of industry experience in machine learning or software engineering, with demonstrated ownership of production ML systems operating at scale
• Proven experience building and scaling ML systems in personalization, relevance, search, or ad tech domains
• Strong hands-on expertise in distributed systems, data pipelines, and ML infrastructure
• Experience deploying ML models into production and operating them at consumer scale
• Demonstrated ownership of complex technical initiatives within a team
• Strong systems design skills with the ability to clearly articulate tradeoffs and implementation decisions
• Experience mentoring engineers and influencing technical standards within a team
• Ability to operate effectively in ambiguous environments and drive projects to completion
• Bachelor's degree in Computer Science, Engineering, or a related technical field
• subject to appropriate work authorization
• Familiarity with LLMs and their application in personalization, feature generation, or search
• Experience with real-time or streaming ML systems
• Exposure to experimentation frameworks (A/B testing) and model performance measurement
• Experience bridging model development with real-time serving systems