NLP / LLM Scientist – Applied AI ML Lead – Machine Learning Centre of Excellence

NLP PEOPLE
London, United Kingdom
4 months ago
Applications closed

Related Jobs

View all jobs
Spotlight

Machine Learning Engineer (Forward Deployed)

Mind Foundry Oxford/ Hybrid, Oxfordshire, United Kingdom
Spotlight

Forward Deployed Engineer

SolveAI London, United Kingdom
Hybrid

Data Scientist / AI Engineer

Searchability NS&D Cheltenham, United Kingdom
£45,000 – £95,000 pa On-site Clearance Required

Senior Data Scientist

Faculty AI London, United Kingdom
Remote Clearance Required

Machine Learning Research Engineer

Luminance Cambridge, United Kingdom
Hybrid

Data Scientist

Faculty AI London, United Kingdom
Hybrid
Posted
11 Jan 2026 (4 months ago)

NLP / LLM Scientist – Applied AI ML Lead – Machine Learning Centre of Excellence

The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.

The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

Job Responsibilities
• Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
• Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, time-series predictions or recommendation systems
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
• Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business

Required qualifications, capabilities, and skills
• Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods
• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field
• Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
• Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
• Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills
• Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
• Knowledge in search/ranking, Reinforcement Learning or Meta Learning
• Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal

About MLCOE
The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning

For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe. To learn about how we’re using AI/ML to drive transformational change, please read this blog: https://www.jpmorgan.com/insights/technology/technology-blog?source=cib_di_jp_aBtechblog102

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company’s data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

Company:

Chase- Candidate Experience page

Qualifications:Language requirements:Specific requirements:Educational level:Level of experience (years):

Senior (5+ years of experience)

Tagged as: Big Data, Industry, Natural Language Processing, NLP, Speech Recognition, United Kingdom


#J-18808-Ljbffr

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise AI Jobs in the UK (2026 Guide)

Where to advertise AI jobs UK in 2026: the specialist boards and communities that reach AI engineers, ML scientists and applied research talent in the UK. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

AI Jobs UK 2026: What to Expect Over the Next 3 Years

AI Jobs UK 2026: roles, salaries and the generative AI, machine learning and applied AI hiring trends shaping UK artificial intelligence careers. Artificial intelligence is creating jobs faster than the market can name them. New roles are appearing every quarter, existing titles are splitting into specialisms, and the technologies underpinning it all are evolving at a pace that makes even last year's job descriptions feel dated. For job seekers, this presents a genuinely unusual challenge. In most industries, career planning means understanding a relatively stable landscape and working out where you fit within it. In AI, the landscape itself is being redrawn in real time. The roles with the most hiring activity in 2028 may not yet have a widely agreed job title in 2026. That's not a reason to feel overwhelmed — it's a reason to get informed. The candidates who thrive in this market aren't necessarily those with the longest CVs or the most credentials. They're the ones who understand the direction of travel: which skills are gaining value, which technologies are driving employer decisions, and how the definition of an "AI job" is expanding well beyond the tech sector. This article breaks down what the UK AI jobs market is likely to look like over the next three years — covering emerging job titles, the technologies reshaping hiring, the skills employers are prioritising, and how to position yourself ahead of the curve rather than behind it.