Machine Learning Engineer / Data Scientist – LLM Agents Job in Springer Nature

Machine Learning Engineer / Data Scientist – Llm Agents

London, ENG, GB, United Kingdom

https://www.mncjobs.co.uk/company/springer-nature

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Job 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