Software Engineer - AI MLOps Oxford, England, United Kingdom

Ellison Institute, LLC
Oxford
18 hours ago
Create job alert

The Ellison Institute of Technology (EIT) Oxford’s purpose is to have a global impact by fundamentally reimagining the way science and technology translate into end-to-end solutions and delivering these solutions in programmes and platforms that respond to humanity’s most challenging problems.

EIT Oxford will ensure scientific discoveries and pioneering science are turned into products for the benefit of society that can have high-impact worldwide and, over time, be commercialised to ensure long-term sustainability.

Led by a world-class faculty of scientists, technologists, policy makers, economists and entrepreneurs, the Ellison Institute of Technology aims to develop and deploy commercially sustainable solutions to solve some of humanity’s most enduring challenges. Our work is guided by four Humane Endeavours: Health, Medical Science & Generative Biology, Food Security & Sustainable Agriculture, Climate Change & Managing Atmospheric CO2 and Artificial Intelligence & Robotics.

Set for completion in 2027, the EIT Campus in Littlemore will include more than 300,000 sq ft of research laboratories, educational and gathering spaces. Fuelled by growing ambition and the strength of Oxford’s science ecosystem, EIT is now expanding its footprint to a 2 million sq ft Campus across the western part of The Oxford Science Park. Designed by Foster + Partners led by Lord Norman Foster, this will become a transformative workplace for up to 7,000 people, with autonomous laboratories, purpose-built laboratories including a plant sciences building and dynamic spaces to spark interdisciplinary collaboration.

The Role

We are seeking Software Engineers to build robust, scalable software systems that power EIT’s scientific initiatives. You will contribute to the full software lifecycle—from architectural design and API development to testing and deployment—ensuring our technology stack is reliable, modular, and built to the highest engineering standards.

Day-to-Day, you might:
  • Design and build robust backend services, APIs, and software modules that power scientific applications and products.
  • Bridge diverse components, integrating ML inference servers, hardware interfaces, and data pipelines into cohesive systems, while ensuring high availability and low latency.
  • Own the full production path—from architectural design and coding to automated testing, benchmarking, deployment, and observability.
  • Collaborate effectively within a multi-disciplinary team of Data Engineers, AI Scientists, Software Engineers and Domain Experts.
  • Champion software engineering best practices maintaining high standard of code quality, system security, and transparency.
What makes you a great fit:
  • MSc or equivalent experience in Computer Sciences, Software Engineering, or a related technical discipline.
  • Extensive experience as a Software Engineer, with required proficiency in Python, including proven success in implementing and deploying robust, scalable distributed systems in production.
  • Demonstrated experience designing, managing, and orchestrating complex systems involving scalable data infrastructure, hardware interfaces, and machine learning models. Expertise in defining and exposing functionality via clean, well-documented APIs (e.g., REST, gRPC).
  • Proven experience implementing and managing robust CI/CD pipelines and reproducible development workflows.
  • Strong collaborator able to clearly communicate system design, architecture decisions, and software engineering practices to multi-disciplinary teams.
You may also have:
  • Experience leveraging Kubernetes for application deployment, and familiarity with distributed computing frameworks (e.g., Ray, Spark), or specialised batch schedulers/resource managers (e.g., Slurm, Volcano, Kueue).
  • Demonstrated expertise with specialised serving engines (e.g., vLLM, Triton) or techniques for deploying models in resource-constrained or high-throughput environments.
  • Experience managing and deploying production systems across diverse environments, including cloud, on-premises clusters, and edge devices.
  • Proven ability to thrive in fast-paced, dynamic R&D settings, demonstrating high autonomy necessary to translate scientific objectives into high-quality software.
We offer the following salary and benefits:
  • Enhanced holiday pay
  • Pension
  • Life Assurance
  • Income Protection
  • Private Medical Insurance
  • Hospital Cash Plan
  • Therapy Services
  • Perk Box
  • Electric Car Scheme
Why work for EIT:

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!


#J-18808-Ljbffr

Related Jobs

View all jobs

Software & Data Engineer for NHS Data & Research

GenAI Software Engineer/Data Scientist

Software and Data Engineer | Oxford University Hospitals NHS Foundation Trust

Data Scientist / Software Engineer

Data Engineer

Data Engineer - AI & Automation

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.