Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Member of Technical Staff | Agentic Workflows | Large Language Models | Natural Language Processing | Machine Learning | Hybrid, London

Enigma
City of London
4 days ago
Create job alert

Member of Technical Staff | Agentic Workflows | Large Language Models | Natural Language Processing | Machine Learning | Hybrid, London


The Opportunity:

We are seeking a highly skilled Member of Technical Staff to lead the development of advanced agentic workflows that will transform how scientists interact with our platform. You will design autonomous systems capable of navigating complex scientific tasks — from retrieving structural biology data to designing molecular binders — entirely through natural language conversation. In this role, you will architect and deploy intelligent agents that democratise access to powerful computational biology tools, enabling researchers worldwide to leverage cutting-edge models via intuitive chat interfaces.


Who We Are:

We are building next-generation generative models that learn the fundamentals of biology. Our team pursues ambitious scientific goals with curiosity and a deep commitment to research excellence. Team members have previously contributed to foundational work in AI-driven biology, generative modeling, and large-scale data infrastructure. You will join a multidisciplinary group of experts in machine learning, life sciences, and software engineering.


Our culture values interdisciplinary exchange, continuous learning, and collaboration. Regular team offsites foster trust and creativity across our distributed locations. We’re looking for innovators passionate about tackling complex challenges and driving global scientific progress.


Who You Are:

  • You are a strong software engineer with deep experience in Python, API design, and distributed systems architecture.
  • You have extensive experience in LLM orchestration, including hands-on use of major LLM APIs and frameworks such as LangChain or LlamaIndex, or you’ve built custom agent frameworks from scratch.
  • You understand intelligent information retrieval, with experience in RAG (Retrieval-Augmented Generation), vector databases, and embedding models for knowledge extraction.
  • You can architect complex workflows using orchestration tools such as Airflow, Prefect, or Temporal, or by building bespoke pipeline systems for multi-step autonomous processes.
  • You bridge science and engineering — comfortable with scientific computing libraries (NumPy, SciPy, pandas) and familiar with scientific databases and literature formats.


What Sets You Apart:

  • You have a research background — perhaps as a former academic researcher or research software engineer in ML/AI.
  • You’re passionate about scientific automation and have experience with document processing, OCR, and data extraction from academic sources.
  • You understand the research ecosystem, including academic and pharmaceutical workflows.
  • You have expertise in NLP, particularly for scientific text processing and citation networks.


Your Responsibilities:

  • Build autonomous scientific agents capable of executing complex research workflows via natural language interaction — from structural analysis to experimental design.
  • Architect end-to-end agentic systems integrating platform capabilities with intelligent decision-making, enabling users to perform sophisticated tasks through simple chat interfaces.
  • Develop knowledge discovery pipelines that autonomously mine scientific literature, identify disease pathways, and propose potential therapeutic targets.
  • Create scalable scientific content by building agents that design experiments, generate hypotheses, and draft research-grade materials.
  • Pioneer autonomous lab workflows through agents that design and validate complex biological systems.
  • Collaborate with scientists to translate research pain points into automation solutions.
  • Publish and present novel applications of agentic workflows in computational biology and related fields.


Apply:

We offer competitive compensation and benefits, including:

  • Private health insurance
  • Pension or retirement contributions
  • Generous leave policies, including gender-neutral parental leave
  • Hybrid work arrangements
  • Opportunities for professional travel


We provide a stimulating environment and the chance to shape the future of biology through breakthrough applications of generative AI. We welcome applicants from all backgrounds and are committed to building a diverse and inclusive team.


Member of Technical Staff | Agentic Workflows | Large Language Models | Natural Language Processing | Machine Learning | Hybrid, London

Related Jobs

View all jobs

Member of Technical Staff | Agentic Workflows | Large Language Models | Natural Language Processing | Machine Learning | Hybrid, London

Research Data Scientist | Barts Health NHS Trust

Data Engineering Manager | Moorfields Eye Hospital NHS Foundation Trust

PET Data Analyst and Modeller (Research Associate)

Sport Scientist (Human Data Science)

Machine Learning Engineer – AI Team (Global Digital)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.