Senior Machine Learning Engineer

Fetch is a company dedicated to transforming everyday activities into meaningful rewards, aiming to be the rewards destination for everyone. They are seeking a Senior Machine Learning Engineer to lead a high-impact team focused on personalization, relevance, and ranking, responsible for the technical direction and execution of ML systems.

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:

• 5+ 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
• 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