ML Infrastructure Engineering Manager – Cloud Inference

Apple Inc.; Greater London; On-site; GBP 140,000 - 200,000; Full time

Job summary

Apple Inc. in London is seeking an Engineering Manager for ML Infrastructure to own components of the cloud AI inference stack and lead the teams that build them.

You will hire, grow, and coach engineers, define a credible technical roadmap, and make architectural calls to keep delivery on track across time zones with ML research, hardware, and platform partners. You should be technically credible, able to review designs, and committed to privacy-by-design in a cutting-edge AI platform.

Qualifications

• Experience managing software engineers, including hiring, coaching, feedback, and performance management.
• Strong software engineering background in systems, backend, distributed systems, or platform work.

Responsibilities

• Build, coach, and retain a high-performing, inclusive team: hiring, onboarding, growth, feedback, and performance management.
• Take ownership of one or more areas of the inference stack, and be accountable for their delivery, quality, and technical direction.
• Set and defend a technical roadmap that stays credible as priorities and platforms change, balancing near-term delivery against longer-term investment.
• Partner across engineering, research, hardware, security and privacy, SRE, and product to deliver outcomes that span team boundaries.
• Hold a rigorous engineering bar: honest measurement, reproducible results, operational readiness, incident review, and documentation.
• Represent your team's work to senior leadership, and advocate for the resources and direction it needs.
• Develop technical leads within your team, delegating real architectural ownership rather than retaining it.
• Ensure the team applies privacy-by-design and secure-by-design principles throughout, particularly around what may and may not be observed or logged in a system handling user content.

Job description

Apple Inc. in London is seeking an Engineering Manager for ML Infrastructure to own components of the cloud AI inference stack and lead the teams that build them.

You will hire, grow, and coach engineers, define a credible technical roadmap, and make architectural calls to keep delivery on track across time zones with ML research, hardware, and platform partners. You should be technically credible, able to review designs, and committed to privacy-by-design in a cutting-edge AI platform.