Senior Machine Learning Engineer

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