Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer / Data Scientist – LLM Agents

NLP PEOPLE
Lochgilphead
1 week ago
Applications closed

Related Jobs

View all jobs

Applied AI, Senior/Staff Forward Deployed Machine Learning Engineer - EMEA

Senior Data Scientist, Generative AI Innovation Center, AWS Generative AI Innovation Center

Data Scientist/Senior Data Scientist - Generative AI

Staff Data Scientist - Fraud

Principal Data Scientist I - Agentic Systems

Principal Data Scientist I - Agentic Systems

Role Description We are looking for a machine learning engineer with strong data science expertise to join the team working on large language models for life and natural science problems. Work involves building agentic workflows where LLMs reason, plan and act, as well as developing pipelines to train and fine-tune models. LangGraph is our main framework for agent development; knowledge of other agent stacks is a plus Key Responsibilities Design and build multi-step LLM agents with LangGraph and similar frameworks Create data and ML pipelines for continual pre-training, supervised fine-tuning and RL alignment Deploy models and retrieval services on containerised infrastructure with reliable CI/CD Monitor and improve agent performance with Weights & Biases and internal dashboards Collaborate with scientists and engineers to turn research ideas into working products Required Qualifications BSc, MSc or PhD in Computer Science, Data Science or a related field Strong Python skills with PyTorch, HuggingFace Transformers and Datasets Proven track record fine-tuning and serving large language models in real-world settings Hands-on experience building pipelines with reinforcement-learning algorithms such as PPO and GRPO Competence with containers, automated testing and software-engineering best practice Useful Skills Basic experience with GCP and infrastructure-as-code workflows Hands-on experience using vector, graph and relational databases, plus SQL and data modelling Experience with multimodal models and emerging agent protocols such as MCP and A2A Ability to implement model safety and guard-rail measures Personal Attributes Team player with clear communication Analytical and detail-oriented problem solver Curious and quick to learn new methods Comfortable in a fast-moving research environment Committed to delivering maintainable, reliable software #LI-SS2 We are an ambitious and dynamic organisation, and home to some of the best-known names in research, educational and professional publishing. Working at the heart of a changing industry, we are always looking for great people who care about delivering quality to our customers and the communities we work alongside. In return, you will find that we open the doors to discovery for all our employees – offering opportunities to learn from some of the best in the business, with a culture that encourages curiosity and empowers people to find solutions and act on their instincts. Whether you are at the beginning of your career or are an experienced professional, we invite you to find out more about the roles we offer and explore our current vacancies. We are a global and progressive business, founded on a heritage of trusted and respected brands – including Springer, founded in 1842, Macmillan, founded in 1843 and Nature, first published in 1869. Nearly two centuries of progress and advancement in science and education have helped shape the business we are today. Research and learning continues to be the cornerstone of progress, and we will continue to open doors to discovery through trusted brands and innovative products and services. Springer Nature Group was created in May 2015 through the combination of Nature Publishing Group, Macmillan Education and Springer Science+Business Media.

Company:

1140 Springer-Verlag London Limited

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

Senior (5+ years of experience)

Tagged as: Industry, Language Modeling, Machine Learning, NLP, United Kingdom


#J-18808-Ljbffr

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 Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.