Applied AI ML Engineer (NLP / LLM and Graphs)

HireHi; Greater London; On-site; GBP 120,000 - 160,000; Full time

Job summary

JPMorgan Chase ищет ведущего специалиста по машинному обучению для разработки передовых моделей и их внедрения в бизнес-процессы. Вы будете работать над NLP, распознаванием речи, временными рядами и системами рекомендаций, сотрудничать с командами бизнеса, технологий и комплаенса, а также вести команду инженеров ИИ.

Требуется глубокое понимание ML/DL, опыт работы с крупномасштабными данными и способность управлять проектами в регулируемой среде.

Qualifications

• Докто́рская степень в области точной дисциплины или сопутствующей
• Совершенное владение методами NLP, LLM и анализом графов
• Опыт разработки и внедрения моделей в регуляторной среде

Responsibilities

• Разработка современных моделей машинного обучения для реальных задач: NLP, распознавание речи, аналитика и рекомендации
• Сотрудничество с бизнесом, технологиями, продуктовым менеджментом, юридическим и комплаенсом для развёртывания решений в продакшн
• Лидирование и наставничество команды инженеров искусственного интеллекта, развитие культуры инноваций
• Разработка масштабируемых фреймворков для ускорения применения ML-моделей по бизнес-направлениям
• Изучение методов ML посредством исследований, конференций, экспериментов и обмена знаниями

Skills

NLP

LLM

Graph analytics

Agentic AI

Multi-agent systems

Experiment design

Big data

Model deployment

Cloud computing

Communication

Education

PhD in a quantitative discipline

MS with significant industry or research experience

Tools

None

Job description

Описание

JPMorgan Chase provides financial services, including strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. Its Chief Data & Analytics Office supports the firm’s data and analytics work, while the Machine Learning Center of Excellence develops and shares machine learning solutions for business problems. *Instagram и Facebook принадлежат компании Meta Platforms Inc., деятельность которой признана экстремистской и запрещена на территории РФ

Задачи

Develop state-of-the-art machine learning models for real-world problems, including NLP, speech recognition and analytics, time-series predictions, and recommendation systems Collaborate with Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management teams to deploy solutions into production Lead, mentor, and inspire a team of AI engineers, fostering excellence, innovation, and continuous learning Drive firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across business areas Research and explore machine learning methods through independent study, conferences, experimentation, and participation in the knowledge-sharing community

Требования

• PhD in a quantitative discipline such as Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science; alternatively, an MS with significant industry or research experience in the field
• Strong background in NLP, LLM, and graph analytics, with hands‑on experience and solid understanding of machine learning and deep learning methods
• Hands‑on experience building agentic AI or multi‑agent systems in regulated or compliance-driven environments
• Recent hands‑on experience training and deploying models and pipelines
• Ability to design experiments and training frameworks, and define and evaluate intrinsic and extrinsic model-performance metrics aligned with business goals, focusing on agentic systems and LLM evaluation
• Experience with big data and scalable model training
• Strong written and spoken communication skills for communicating technical concepts and results to technical and business audiences
• Scientific thinking, ability to invent, and ability to work independently and collaboratively
• Curiosity, diligence, attention to detail, and motivation to solve complex analytical problems
• Будет плюсом: strong Mathematics and Statistics background, familiarity with financial services, continuous integration models and unit test development, graph integration with LLM, Reinforcement Learning or Meta Learning, A/B experimentation, data- and metric-driven product development, cloud-native deployment in large-scale distributed environments, ability to develop and debug production-quality code, published research in Machine Learning, Deep Learning, or Reinforcement Learning at a major conference or journal