Staff Machine Learning Engineer - Ad Platform

Fetch; Canada; Remote; CAD 255,000 - 368,000; Full time

Job summary

Fetch is building the future of personalized consumer experiences. We’re seeking a Staff Machine Learning Engineer to own the technical direction and execution for our ML systems, focusing on personalization, relevance, and ranking.

You will lead design and delivery while staying hands-on. You will partner with product and cross-functional teams, mentor engineers, and drive scalable architectures that perform reliably at consumer scale across deployments including real-time serving and

Qualifications

• 12+ years of industry experience in machine learning or software engineering with production ML ownership.
• Proven track record building and scaling ML systems for personalization, relevance, or ad tech.
• Strong hands-on skills in distributed systems, data pipelines, and ML infrastructure.
• Experience deploying ML models to production at consumer scale and driving technical initiatives.
• Ability to mentor engineers and influence technical standards within a team.

Responsibilities

• Serve as the technical lead for a single ML-focused team, setting direction and elevating engineering quality.
• Design, build, and scale ML systems supporting personalization, ranking, search, or ads.
• Own end-to-end architecture for services including model training, evaluation, deployment, and serving.
• Collaborate with product and cross-functional teams to deliver measurable business impact.
• Mentor engineers with hands-on guidance and code reviews, fostering best practices.

Skills

Distributed systems

Data pipelines

ML infrastructure

Technical leadership

Mentoring engineers

Problem solving in ambiguous env

Education

Bachelor’s degree in Computer Science, Engineering, or a related technical field

Job description

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 or any Canadian province (excluding Quebec), subject to appropriate work authorization. Canadian employment, if applicable, would be through Fetch’s Canadian Employer of Record.

Benefits for Canada-based employees may differ slightly to comply with applicable law(s) (e.g., paid time off, Holidays, etc.).

Fetch may use technology tools that incorporate artificial intelligence ("AI") capabilities to support certain activities within our recruiting and hiring process:

• Reviewing and organizing applications and resumes to help our recruiting team manage high volumes of submissions, including automated review of fraud signals to identify bad actors;
• Identifying candidates whose stated qualifications and experience appear relevant to an open position;
• Scheduling and coordinating interviews with candidates;
• Generating interview summaries or notes to assist recruiters and hiring managers in their review; and
• Conducting research on open roles and candidate pools to improve the effectiveness of our recruiting practices.

Fetch does not use AI tools to make hiring decisions. All decisions regarding whether to advance a candidate, extend an offer, or decline an application are made by Fetch employees, who are predominantly members of our Talent Acquisition team and relevant Hiring Managers. AI tools serve only to assist the process of recruiting talent and to inform the human review of candidate information. In no way does Fetch allow AI systems to make, finalize, or override any employment decision