> Markdown version of [/jobs/ext/2243704-research-scientist-diffusion-modelling-python-pytorch-machine-learning-generative-mod](https://www.wearedevelopers.com/jobs/ext/2243704-research-scientist-diffusion-modelling-python-pytorch-machine-learning-generative-mod). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Scientist | Diffusion Modelling | Python | PyTorch | Machine Learning |Generative Mod[...] - **Company:** Enigma - **Location:** UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Computational Biology, Information Engineering, Data Systems, Python (Programming Language), Machine Learning, Rapid Prototyping Process, Raw Data, Pytorch, Deep Learning, Generative AI, Information Technology, Code Testing, Machine Learning Operations, Stable Diffusion, Data Pipelines - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815332262-research-scientist--diffusion-modelling--python--pytorch--machine-learning-generative-mod ## About the Role * You are an effective ML engineer. You write maintainable, well-tested code, use modern development workflows, and are equally comfortable rapid-prototyping and producing high-quality production systems. You have experience training and running large-scale models on cloud or distributed hardware. * You have strong data engineering skills. You can build scalable data pipelines for training and evaluating deep learning models, inspect and refine raw data, design appropriate dataset splits, and ensure data systems perform reliably. * You are deeply motivated by model quality and performance. You understand how frameworks, hardware, and data interact, and you enjoy optimizing model architecture, throughput, and evaluation metrics. * You are mission-driven, adaptable, and intellectually curious. You thrive in fast-moving environments, stay focused on end goals, and approach problems of all sizes with enthusiasm. What Sets You Apart * Experience in computational biology, protein design, or ML applications in the life sciences. * Academic training or professional exposure to natural sciences such as physics, biology, or chemistry. ## Description Founder @ Enigma | Global Machine Learning & Generative AI Recruitment Business Role Overview We are seeking a highly capable machine learning researcher with deep expertise in generative modeling. In this role, you will join an interdisciplinary group of machine learning practitioners, scientists, and engineers working together to advance how we design biological systems and develop new therapeutic approaches. You will be responsible for developing novel generative models aimed at creating functional proteins validated in laboratory settings. Who You Are * You are an experienced ML researcher with a strong background in generative modeling. You have contributed substantially to major machine learning efforts such as open-source libraries, significant product deployments, or impactful scientific publications. * You are an effective ML engineer. You write maintainable, well-tested code, use modern development workflows, and are equally comfortable rapid-prototyping and producing high-quality production systems. You have experience training and running large-scale models on cloud or distributed hardware. * You have strong data engineering skills. You can build scalable data pipelines for training and evaluating deep learning models, inspect and refine raw data, design appropriate dataset splits, and ensure data systems perform reliably. * You are deeply motivated by model quality and performance. You understand how frameworks, hardware, and data interact, and you enjoy optimizing model architecture, throughput, and evaluation metrics. * You are mission-driven, adaptable, and intellectually curious. You thrive in fast-moving environments, stay focused on end goals, and approach problems of all sizes with enthusiasm. What Sets You Apart * Experience in computational biology, protein design, or ML applications in the life sciences. * Academic training or professional exposure to natural sciences such as physics, biology, or chemistry. Your Responsibilities Develop machine learning systems with real-world impact (~90%): * Help curate training and evaluation datasets. * Define and implement evaluation metrics aligned with practical objectives. * Rapidly prototype and iterate on generative modeling approaches. * Collaborate in a shared codebase with colleagues across research and engineering. * Support the infrastructure used for compute, experimentation, and model development. * Work with experimental teams to plan laboratory testing and run model inference for biological targets. Personal and Professional Development (~10%): * Stay informed about the latest advances in machine learning. * Develop working knowledge of protein science and cellular biology. * Participate in internal knowledge-sharing activities. * Attend relevant scientific or technical events. What We Offer * Competitive compensation and benefits * Retirement contributions * Generous leave policies, including inclusive parental leave * Flexible and hybrid working arrangements * Opportunities for travel and professional development We provide a collaborative and intellectually stimulating environment, along with the opportunity to influence the future of biological design through state-of-the-art generative modeling. We encourage applicants from all backgrounds and are committed to fostering a diverse and inclusive team. Seniority level Mid-Senior level Employment type Full-time Job function Information Technology Industries Staffing and Recruiting ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)