Machine Learning Engineer (PyTorch LLM
Role details
Job location
Tech stack
Job description
We are seeking a hands-on Prompt Engineer / LLM Context Engineer to design, build, and iteratively refine prompts, instruction frameworks, and context architectures that govern how large language models behave within enterprise AI applications.
This is a technical engineering role - not creative writing - focused on delivering consistent, accurate, and auditable outputs from LLM systems operating in a regulated life sciences environment.
The successful candidate will work at the intersection of AI engineering, retrieval systems, and domain collaboration, ensuring model outputs are reliable, measurable, and production-ready., Prompt & Instruction Engineering
- Design system prompts, structured instructions, and few-shot examples for production LLM use cases
- Iteratively refine prompts to resolve failures, edge cases, and domain-specific gaps
- Optimize prompt structure for consistency, determinism, and accuracy
Context Engineering & RAG
- Design and manage context pipelines for LLM applications
- Select, rank, and format retrieved content from knowledge bases and document stores
- Work closely with Retrieval-Augmented Generation (RAG) architectures to ground outputs in verified data
- Minimize hallucinations through strong context design
Evaluation Frameworks (Evals)
- Build and maintain systematic evaluation frameworks to measure prompt performance
- Define metrics for accuracy, consistency, and relevance
- Run regression testing and continuous prompt improvement cycles
- Use data-driven insights to guide prompt iteration (40-50% of role focus)
Cross-Functional Collaboration
- Partner with ML engineers, data scientists, and scientific SMEs
- Translate complex life sciences requirements into precise model instructions
- Support integration of LLM capabilities into production workflows
Prompt Governance & Compliance
- Maintain version control and documentation of prompt assets
- Ensure traceability suitable for regulated pharma environments
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Requirements
- Proven hands-on experience engineering prompts for production LLM applications
- Strong understanding of:
- LLM behaviour and instruction following
- Context windows and tokenisation
- Hallucination mitigation techniques
- Practical experience with RAG (Retrieval-Augmented Generation) architectures
- Solid Python skills for scripting, testing, and automation
- Experience building or working with evaluation frameworks ("evals")
- Systematic, metric-driven approach to prompt iteration
- Strong stakeholder communication skills
Highly Desirable
- Experience in life sciences, pharma, or regulated environments
- Familiarity with vector databases and retrieval pipelines
- Experience working with ML/AI engineering teams in production settings
- Understanding of governance requirements in regulated industries
Benefits & conditions
£100,000
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Machine Learning Engineer PyTorch LLM
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