Senior Machine Learning Engineer

CompanyInsight Global

LocationLondon Area, United Kingdom

Posted At1/16/2026

UK Visa Sponsorship Analytics

Occupation Type

Programmers and software development professionals

Occupation Code Skill LevelHigher Skilled

Sponsorship Salary Threshold

£54,700 (£28.05 per hour)

Occupation rate applies

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Description

We are looking for a Senior ML Engineer to lead ML Engineering for a GenAI biological reasoning project for one of our largest Pharmaceutical Manufacturing clients. The initiative has evolved from a POC to a working MVP with agents and foundational data all built on scientific literature. You’ll partner with data scientists and platform teams to scale the MVP to a robust product, strengthen data foundations, and make these NLP capabilities reusable across R&D. The ideal candidate thrives on LLM and agent systems, Graph RAG, and building operational excellence on AWS without SageMaker. In addition, you will guide key technical decisions as the model grows and communicating clearly with research scientists and IT stakeholders.

Responsibilities Include:

Lead the ML engineering path from POC/MVP to production for the scientific literature reasoning platform
Decide on approaches and architectures for LLMs, agents, RAG/Graph RAG, and knowledge graph integrations
Implement performance strategies, evaluations, guardrails, and runtime optimisations to ensure LLM performance remains high
Evolve and harden the NLP data foundations to make them replicable for other teams and use cases

Build text-mining and processing pipelines over large scientific literature corpora

Work closely with Data Scientists, Researchers, Data Engineering and senior stakeholders on a daily basis

Deliver on AWS and support the Databricks transition over the coming months

Contribute to a fail‑proof foundation where the capabilities of the model remain valuable even if this specific use case is deprioritized

Qualifications:

Senior or SME-level ML Engineering experience with ownership of LLM and agent systems
Specifically end‑to‑end experience building text‑only ML/LLM systems
Advanced Python and strong software engineering practices such as version control, CI/CD and testing
Very comfortable being hands-on with LLM frameworks, such as LangChain, LangGraph, DSPy and LlamaIndex
Proven experience with RAG, especially Graph RAG for text, knowledge-graph traversal and graph ML
Track record of building systems for complex reasoning and research tasks including the architecture as well as the implementation
Biomedical NLP expertise and comfort with text-mining and processing of unstructured data

Ability to collaborate and communicate effectively with Data Scientists, IT Operations, and Data Engineering

Experienced delivering ML systems on AWS without using SageMaker

Plusses:

Experience working with scientific literature or life‑sciences R&D text
Familiarity with transitioning workloads to Databricks and making foundational NLP platforms reusable across teams.
Previous experience working for enterprise pharmaceutical companies
PhD or master's degree in a relevant field