Machine Learning Engineer / Data Scientist – LLM Agents

NLP PEOPLE; Crinan; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading company in research and publishing is seeking a machine learning engineer to advance their work on large language models. Ideal candidates will have strong Python skills, experience with algorithms like PPO, and a proven track record in deploying models. Join a dynamic team committed to delivering quality and innovation in science and education.

Qualifications

• Strong Python skills with experience in ML frameworks.
• Proven track record with large language models.
• Hands-on experience with reinforcement learning algorithms.

Responsibilities

• Design and build LLM agents using LangGraph.
• Create ML pipelines for continuous training.
• Deploy models in a containerized infrastructure.

Skills

Python

PyTorch

HuggingFace Transformers

Reinforcement Learning

SQL

Education

BSc, MSc or PhD in Computer Science, Data Science or a related field

Tools

GCP

Automated Testing

Vector Databases

Job description

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