Staff Machine Learning Engineer
Leads ML team building scalable systems for personalization, ranking, search, and ads. Owns end-to-end architecture from training to serving at consumer scale, requiring 8+ years ML experience and strong systems design skills.
About the job
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
- 8+ 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.
Skills
Machine Learning, LLMs, Distributed Systems, Data Pipelines, ML Infrastructure, Model Training, Model Deployment, Model Serving, Personalization, Ranking, Search, A/B Testing, System Design
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