Research Engineer - Model Ablation AI & Robotics England, United Kingdom

Job summary

Autonomous Labs is building the next generation of AI-driven scientific laboratories, with the mission of automating the entire scientific discovery workflow - from experimental design and execution to analysis and iterative learning. Foundation models are a core component of this vision, enabling intelligent, adaptive, and autonomous scientific experimentation.

• Drive technical work on improving the performance of frontier foundation models - both autoregressive foundation models and world models - for autonomous scientific experimentation.
• Conduct research into the interactions between training data and foundation models to identify the key factors limiting model performance, and develop novel data-centric approaches for continuous improvement.
• Define and source the data needed to move model performance, working closely with domain experts across the laboratory to specify, collect, and curate high-value experimental datasets.
• Design and maintain scalable experimentation pipelines for model training, evaluation, benchmarking, and reproducible research.
• Analyse experimental results using rigorous scientific methodologies and translate insights into actionable improvements for model performance in a data-centric way.
• Collaborate closely with AI researchers, software engineers, robotics engineers, and scientific domain experts to ensure research findings translate into impactful real-world scientific capabilities.
• Contribute novel research ideas and publish high-quality research where appropriate, while maintaining a strong focus on practical deployment.
• Communicate experimental findings and technical insights clearly across interdisciplinary teams to help shape the future direction of the Auto Lab AI platform.

• MSc, PhD, or equivalent industry experience in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related discipline.
• Hands-on experience with frontier foundation models, including autoregressive foundation models such as Large Language Models (LLMs), Vision-Language Models (VLMs) and Vision-Language-Action (VLA) models, as well as embodied AI models and world models.
• Experience with continuous pre-training, post-training, supervised fine-tuning, reinforcement learning, and other foundation model optimisation techniques.
• Hands-on experience building end-to-end machine learning pipelines, including data curation, data mixing, model training, evaluation, performance analysis, and iterative model improvement.
• Experience working within interdisciplinary teams.
• Excellent written and verbal communication skills, with the ability to communicate complex experimental findings clearly across disciplines.
• An impact-driven mindset with a passion for continuously improving model performance for real world deployment.

In rough order of desirability.

• Research experience in embodied AI and robotics.
• Research or engineering experience with world models, model-based reinforcement learning, or learned simulators.
• Experience in working with scientific domain experts.
• Experience with large-scale distributed training infrastructure.
• Publications at leading AI conferences (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, RSS, or equivalent).
• Experience working with large multimodal datasets, robotics datasets, or scientific datasets. Experience building scalable and reproducible experimentation and evaluation frameworks.

• Curious and analytical, with a passion for understanding why foundation models succeed or fail.
• Strong scientific thinking combined with practical engineering skills.
• Comfortable working in an iterative, fast-paced research environment.
• Collaborative and proactive, with the ability to work effectively across AI, robotics, software engineering, and scientific disciplines.
• Organised, resourceful, and capable of managing multiple experimental projects simultaneously.
• Mission-driven, with a desire to accelerate scientific discovery through frontier AI research.

Enhanced holiday pay

Pension

Life Assurance

Income Protection

Private Medical Insurance

Hospital Cash Plan

Therapy Services

Perk Box

Electric Car Scheme

--

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!