Senior Staff ML Engineer - Scale ML Systems Leader

Meta; Greater London; On-site; GBP 180,000 - 240,000; Full time

Job summary

Meta is advancing shopping tech across Facebook, Instagram, and Muse, building a scalable Product Recognition and Intelligence stack. You will lead the journey to train, serve, and evaluate ML models that touch billions of users and items, set architectural standards, and ship production-ready systems across the organization.

You will tackle hard ML systems challenges, influence direction across teams, and contribute to responsible AI practices while delivering high-impact improvements that

Qualifications

• Experience designing, building, and operating large-scale ML systems in production.
• Experience architecting infrastructure components for ML at scale.
• Experience improving ML systems across multiple teams and abstractions.
• Proven ability to influence technical direction and set engineering standards.
• Experience building large-scale object recognition models.
• Ability to translate research advances into production systems.
• Active work on AI tooling, observability, and lifecycle tooling.

Responsibilities

• Lead the design and governance of the ML platform used for production models.
• Architect and implement scalable training, serving, and evaluation pipelines.
• Collaborate across engineering teams to raise architectural standards.
• Ship state-of-the-art models and ensure reliable, ethical AI practices.

Skills

Large-scale ML systems

Distributed training pipelines

Model serving systems

ML evaluation frameworks

Platform migrations

AI observability

Prompt/context engineering

Agent orchestration

Cross-team collaboration

Responsible AI practices

Job description

Meta is advancing shopping tech across Facebook, Instagram, and Muse, building a scalable Product Recognition and Intelligence stack. You will lead the journey to train, serve, and evaluate ML models that touch billions of users and items, set architectural standards, and ship production-ready systems across the organization.

You will tackle hard ML systems challenges, influence direction across teams, and contribute to responsible AI practices while delivering high-impact improvements that