Research Engineer

Location: Oxford, England, United Kingdom

Department: AI & Robotics

Workplace: hybrid

Employment Type: full

Description

Join us at EIT:

At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges in four transformative areas:

• Health, Medical Science & Generative Biology
• Food Security & Sustainable Agriculture
• Climate Change & Managing CO₂
• Artificial Intelligence & Robotics

This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas for lab to society. Explore more at www.eit.org.

We are currently hiring for multiple positions across multiple specialised tracks. 

Foundation Models for Embodied AI 

This team focuses on developing the next generation multimodal models that connect virtual and physical environments. You will advance the frontier of scientific workflows by integrating AI with robotics and sensor data with the goal to advance scientific discovery. 

• Focus: LLMs,  VLMs, and Vision-Language-Action (VLA) models. 

• Key Challenge: Developing multi-modal models and agentic AI that can reason across modalities and translate digital intelligence into physical-world impact. 

• Ideal Background: Experience with large scale autoregressive models, deep reinforcement learning, generative models, multimodal models and/or robotics-related AI systems. 

Foundational Models for Health & Life Science 

This team works at multi-scale level, from molecules to patient-level data, utilizing large-scale datasets—including proteins, DNA, EHR and medical images—to design advanced ML architectures for healthcare and biological discovery. 

• Focus: Multimodal generative models (LLMs, diffusion, flows) across patient and biomolecular datasets,physics-based molecular modelling. 

• Key Challenge: Building scalable ML systems that incorporate various sources of data, long contexts and HPC simulations to solve complex biological modelling problems. 

• Ideal Background: Proficiency in GPU-based computing , with an advanced degree in CS, Physics, Chemistry, or Materials Science. 

Core Responsibilities 

Regardless of the track, you will be expected to: 

• Design & Deploy: Build, train, and optimize advanced ML architectures and foundation models. 

• Bridge the Gap: Translate high-level research ideas into scalable, reliable, and reproducible systems. 

• Collaborate: Work in cross-disciplinary squads alongside roboticists, biologists, data domain experts and software architects. 

• Execute: Maintain high standards of code quality and drive the technical implementation of mission-critical projects. 

Requirements

Qualifications & Skills 

Universal Requirements: 

• Degree in Computer Science, Physics, Chemistry, or Materials Science with a strong ML focus. 

• A strong bias toward execution and impact in a mission-driven environment. 

• Mastery of deep learning frameworks (e.g., PyTorch) and experience delivering large-scale AI projects. 

• Exceptional communication skills to bridge the gap between technical and non-technical stakeholders. 

Track-Specific Expertise: 

• For Embodied AI: Demonstrated excellence in delivering multimodal or agentic AI systems; experience with robotics hardware or simulation is a significant bonus. 

• For Health: Experience with biomolecular datasets, medical and life science imaging datasets, HPC integrations, and distributed system architectures, biomolecular modelling. 

Benefits

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

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