National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

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

NLP PEOPLE
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Associate AI Researcher - Natural Language Processing

Data Scientist LLM (m/f/d)

Junior Data Scientist

Principal Data Scientist

Machine Learning Engineer (AGI ), AGI Vertical Service Inference & Engine

Machine Learning Performance Engineer

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

  1. Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community.
  2. 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.
  3. Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
  4. 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

  1. 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.
  2. 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.
  3. Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
  4. Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
  5. 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.
  6. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
  7. Curious, hardworking and detail-oriented, and motivated by complex analytical problems.

Preferred Qualifications, Capabilities, and Skills

  1. Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.
  2. Knowledge in search/ranking, Reinforcement Learning or Meta Learning.
  3. 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.
  4. 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 visitthis link. To learn about how we’re using AI/ML to drive transformational change, please readthis blog.

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

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

How to Find Hidden AI Jobs in the UK Using Professional Bodies like BCS, IET & the Turing Society

When it comes to job hunting in artificial intelligence (AI), most candidates head straight to traditional job boards, LinkedIn, or recruitment agencies. But what if there was a better way to find roles that aren’t advertised publicly? What if you could access hidden job leads, gain inside knowledge, or get referred by people already in the field? That’s where professional bodies and specialist AI communities come in. In this article, we’ll explore how UK-based organisations like BCS (The Chartered Institute for IT), IET (The Institution of Engineering and Technology), and the Turing Society can help you uncover AI job opportunities you won’t find elsewhere. We'll show you how to strategically use their directories, special-interest groups (SIGs), and CPD (Continuing Professional Development) events to elevate your career and expand your AI job search in ways most job seekers overlook.

How to Get a Better AI Job After a Lay-Off or Redundancy

Being made redundant or laid off can feel like the rug has been pulled from under you. Whether part of a wider company restructuring, budget cuts, or market shifts in tech, many skilled professionals in the AI industry have recently found themselves unexpectedly jobless. But while redundancy brings immediate financial and emotional stress, it can also be a powerful catalyst for career growth. In the fast-evolving field of artificial intelligence, where new roles and specialisms emerge constantly, bouncing back stronger is not only possible—it’s likely. In this guide, we’ll walk you through a step-by-step action plan for turning redundancy into your next big opportunity. From managing the shock to targeting better AI jobs, updating your CV, and approaching recruiters the smart way, we’ll help you move from setback to comeback.

AI Jobs Salary Calculator 2025: Work Out Your Market Value in Seconds

Why your 2024 salary data is already outdated “Am I being paid what I’m worth?” It is the question that creeps in whenever you update your CV, see a former colleague announce a punchy pay rise on LinkedIn, or notice a recruiter slide into your inbox with a role that looks eerily similar to your current one—only advertised at £20k more. Artificial intelligence moves faster than any other hiring market. New frameworks are open‑sourced overnight, venture capital floods specific niches without warning, & entire job titles—Prompt Engineer, LLM Ops Specialist—appear in the time it takes most industries to schedule a meeting. In that environment, salary guides published only a year ago already look like historical curiosities. To give AI professionals an up‑to‑the‑minute benchmark, ArtificialIntelligenceJobs.co.uk has built a simple yet powerful salary‑calculation formula. By combining three variables—role, UK region, & seniority—you can estimate a realistic 2025 salary band in less than a minute. This article explains that formula, unpacks the latest trends driving pay, & offers concrete steps to boost your personal market value over the next 90 days.