Machine Learning Engineer, AI & Data Platforms (AiDP)

Apple, Inc.

Greater London

On-site

GBP 120,000 - 180,000

Full time

14 days+

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Job summary

Apple ищет опытного ML‑инженера в Лондон для разработки и развёртывания LLM‑систем, их обучения, калибровки и внедрения в масштабируемые продукты на Python, Swift и Java. Экспертиза в RLHF/LoRA и оценке моделей обязательна; вы будете устанавливать инженерные стандарты и работать в кросс‑функциональной команде.

Кандидаты должны иметь мощный опыт разработки ML‑пайплайнов, а также умение проектировать продакшн‑инфраструктуру и участвовать в создании пользовательских решений на глобальном уровне.

Qualifications

  • Обширный практический опыт ML-инжиниринга с выпущенными ML‑продуктами.
  • Практика тонкой настройки LLM, выравнивания и кастомизации (RLHF, LoRA, QLoRA).
  • Сильное владение Python, Swift и Java.
  • Опыт построения и эксплуатации ML‑пайплайнов в облаке или on‑prem.

Responsibilities

  • Ведение разработки и продакшн‑постановки LLM‑систем от upstream‑обучения до развёртывания.
  • Проектирование и внедрение фреймворков оценки моделей по качеству, безопасности и стоимости.
  • Архитектура инференс‑инфраструктуры и оптимизация моделей.
  • Разработка стратегий кастомизации и обучения моделей, включая prompt‑engineering и retrieval‑augmented generation.
  • Создание end‑to‑end AI‑продуктов и фич на Swift, Java и Python.
  • Установка стандартов разработки, тестирования и CI/CD для пайплайнов.
  • Сотрудничество с исследованиями, продуктом и дизайном для масштабируемых решений.
  • Менторство инженеров ML и развитие исследовательской культуры.

Skills

ML engineering
LLM fine-tuning
RLHF & LoRA
Prompt optimization
Python proficiency
Swift proficiency
Java proficiency

Tools

Python
Swift
Java

Job description

Описание:

Apple builds AI systems that shape experiences for billions of people, with a commitment to privacy, performance, and craft. Its AI & Data Platforms team develops generative AI systems and products at global scale.

Задачи:
  • Lead the end-to-end development and productionisation of LLM-based systems, from upstream training and reinforcement learning through fine-tuning, alignment, and deployment of globally scaled products
  • Design and implement LLM evaluation and benchmarking frameworks to assess model quality, safety, bias, latency, and cost-efficiency
  • Architect production inference infrastructure, including model optimisation, quantisation, and efficient serving strategies
  • Drive model customisation and adaptation strategies, including prompt engineering, retrieval-augmented generation, and parameter-efficient and full fine-tuning
  • Build end-to-end AI-powered products and features, owning delivery from problem definition and prototyping through production release across Swift, Java, and Python codebases
  • Establish engineering standards across the ML development lifecycle, including testing, reproducibility, monitoring, documentation, and CI/CD for model and data pipelines
  • Partner with research, product, design, and platform teams to turn emerging capabilities into scalable, user-centric solutions
  • Mentor ML engineers, raise technical quality, and foster rigorous experimentation and engineering craft
Требования:
  • Extensive hands-on Machine Learning engineering experience and a track record of shipping ML-powered products at scale
  • Practical expertise in LLM fine-tuning, alignment, and customisation, including RLHF, LoRA, QLoRA, prompt optimisation, and LLM evaluation and benchmarking
  • Strong software engineering proficiency in Python, Swift, and Java
  • Experience building and operating enterprise-grade ML pipelines in cloud or on-prem environments
  • Будет плюсом: end-to-end AI product delivery, published papers in top ML/Statistics/Maths/computer science conferences, LLM pre-training, reinforcement learning for model alignment, safety and red-teaming, agentic frameworks, multimodal AI systems, standalone AI-native products, open-source contributions, research or patents, inference optimisation, data engineering, architectural direction, cross-team alignment, and mentoring senior engineers
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