Staff Machine Learning Engineer

fetch; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Fetch is seeking a Staff Machine Learning Engineer to act as the technical lead for a high-impact ML team focused on personalization, relevance, and ranking. You will own the technical direction and execution for ML systems, guiding architecture and deployment while staying hands-on in design and development.

You will partner with product, data, and engineering stakeholders to deliver measurable business impact, mentor engineers, and explore LLM tools to accelerate development and improve system

Qualifications

• 12+ years of industry experience in machine learning or software engineering.
• 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.

Responsibilities

• Serve as the technical lead for a single ML-focused team, setting direction and engineering quality.
• Design, build, and scale ML systems supporting personalization, ranking, search, or ad-related use cases.
• Own end-to-end architecture for services, including model training, evaluation, deployment, and serving.
• Drive clarity in ambiguous problem spaces and translate product needs into scalable technical solutions.
• Lead design reviews and balance latency, reliability, experimentation, and maintainability.

Skills

Machine Learning

Distributed Systems

Leadership

Production ML

Mentoring

Education

Bachelor's degree in CS/Engineering or related

Job description

What we’re building and why we’re building it

About the Role

Fetch is building the future of personalized consumer experiences. We’re looking for a Staff Machine Learning Engineer to serve as the technical lead for a high-impact ML team focused on personalization, relevance, and ranking.

In this role, you will own the technical direction and execution for your team’s ML systems - driving high-quality architecture, guiding implementation, and ensuring models and infrastructure operate reliably at scale. You’ll partner closely with product and cross-functional stakeholders while remaining deeply hands‑on in design and development.

Role 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.

Minimum 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.

Preferred Requirements

• 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.

This is a full‑time role that can be held from one of our US offices or remotely in the United States.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.