Principle Machine Learning Engineer, AI & Data Platforms (AiDP)
UK Visa Sponsorship Analytics
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Occupation Type
Programmers and software development professionals
Occupation Code Skill LevelHigher Skilled
Sponsorship Salary Threshold
£54,700
(£28.05 per hour)
Occupation rate applies
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Description
Summary
At Apple, we build AI systems that define experiences for billions of people and we do it with an unwavering commitment to privacy, performance, and craft. The AI & Data Platforms (AiDP) team is seeking a Principle Machine Learning Engineer to lead the design, fine-tuning, evaluation, and productionisation of large language models and generative internal AI systems at global scale. This is a deeply hands-on, high-impact role: you will work across the full model lifecycle, from reinforcement learning and upstream training through to deployment of standalone, customer-facing products.
The ideal candidate is equal parts researcher, engineer, and product builder. You bring authoritative depth in LLM customisation and alignment, a sharp instinct for performance and quality, and the ability to ship end-to-end AI-powered products that meet Apple's standard of excellence.
If you thrive at the intersection of frontier model development, systems engineering, and product creation we want to hear from you.
Description
Our Principle Machine Learning Engineers are technical leaders who shape the direction of intelligent systems across Apple. In this role, you will own the end-to-end lifecycle of an internal generative AI System at global scale - from pre-training LLM strategies and reinforcement learning from human feedback (RLHF) through fine-tuning, alignment, evaluation, and production deployment. You will
At Apple, we build AI systems that define experiences for billions of people and we do it with an unwavering commitment to privacy, performance, and craft. The AI & Data Platforms (AiDP) team is seeking a Principle Machine Learning Engineer to lead the design, fine-tuning, evaluation, and productionisation of large language models and generative internal AI systems at global scale. This is a deeply hands-on, high-impact role: you will work across the full model lifecycle, from reinforcement learning and upstream training through to deployment of standalone, customer-facing products.
The ideal candidate is equal parts researcher, engineer, and product builder. You bring authoritative depth in LLM customisation and alignment, a sharp instinct for performance and quality, and the ability to ship end-to-end AI-powered products that meet Apple's standard of excellence.
If you thrive at the intersection of frontier model development, systems engineering, and product creation we want to hear from you.
Description
Our Principle Machine Learning Engineers are technical leaders who shape the direction of intelligent systems across Apple. In this role, you will own the end-to-end lifecycle of an internal generative AI System at global scale - from pre-training LLM strategies and reinforcement learning from human feedback (RLHF) through fine-tuning, alignment, evaluation, and production deployment. You will
architect and deliver standalone AI-powered products and platform capabilities that operate reliably at global scale.
You will establish rigorous benchmarking and evaluation frameworks to measure LLM performance across accuracy, latency, safety, and fairness dimensions. You will drive model customisation strategies, including prompt engineering, parameter-efficient fine-tuning (LoRA, QLoRA), and full fine-tuning, tailored to diverse product requirements. You will design and build production-grade inference systems, working across Swift, Java, and Python to integrate ML capabilities seamlessly into Apple's ecosystem. As a senior technical contributor, you will set engineering standards, mentor engineers, and influence the technical roadmap for generative AI adoption across the organisation.
Responsibilities
You will establish rigorous benchmarking and evaluation frameworks to measure LLM performance across accuracy, latency, safety, and fairness dimensions. You will drive model customisation strategies, including prompt engineering, parameter-efficient fine-tuning (LoRA, QLoRA), and full fine-tuning, tailored to diverse product requirements. You will design and build production-grade inference systems, working across Swift, Java, and Python to integrate ML capabilities seamlessly into Apple's ecosystem. As a senior technical contributor, you will set engineering standards, mentor engineers, and influence the technical roadmap for generative AI adoption across the organisation.
Responsibilities
- Lead the end-to-end development and productionisation of LLM-based systems, from upstream training and reinforcement learning (RLHF/RLAIF) through fine-tuning, alignment, and deployment of standalone, globally scaled products
- Design and implement comprehensive LLM evaluation and benchmarking frameworks, assessing model quality, safety, bias, latency, and cost-efficiency to inform model selection and customisation decisions
- Extensive hands-on Machine Learning engineering experience, with a demonstrable track record of shipping ML-powered products at scale
- Deep, practical expertise in LLM fine-tuning, alignment, and customisation - including reinforcement learning from human feedback (RLHF), parameter-efficient fine-tuning (LoRA, QLoRA), prompt optimisation and LLM evaluation and benchmarking strategies (accuracy, latency, safety, cost)
- Strong software engineering proficiency across Python, Swift, and Java, with the ability to contribute production-quality code across Apple's technology stack
- Experience building and operating enterprise-grade ML pipelines (data preparation, distributed training, model optimisation, serving, and monitoring) in cloud (AWS, GCP, Azure) or on-prem environments
- Demonstrated ability to deliver end-to-end AI products - from problem framing and experimentation through to globally deployed, production-grade solutions
- Published papers in top conferences in ML/Statistics/Maths/compsci.
- Experience with pre-training or continued pre-training of large language models, including data curation, curriculum design, and training stability at scale
ployer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more