Research Engineer

Oxford Dynamics is at an inflection point. We operate in some of the most complex and high-stakes environments in the world: defence, national security, and incident response. The decisions we make now will define not just how fast we grow, but who we become.

We know that the best people don’t always arrive in time for a specific job ad. If you’re excited by ownership, pace and purpose, and by building something that genuinely matters, we’d love to hear from you, even if you don’t see a live role that fits.

Who we are

Founded in 2020, Oxford Dynamics is a fast-growing UK deep-tech company developing both digital AI and physical AI systems designed to operate in dynamic, mission-critical environments.

Our flagship AVIS (AVIS, A Very Intelligent System) platform fuses multi-modal data, including text, imagery, telemetry, and sensor feeds, enabling operators to interrogate complex information at speed and make better decisions under pressure. We apply AVIS in the real world through platforms like STRIDER for CBRN applications and BARBARIAN for explosive ordnance detection.

Our ambition is simple but demanding: to converge AI and robotics so machines can sense, understand, and act in complex, real-world environments. We work with defence and security organisations internationally to help protect nations, infrastructure, and lives.

Core Brief:

You will help convert OD’s research into capabilities that ship into some of the most demanding environments in the world. The role offers a rare combination: frontier ML research, real engineering ownership, and a direct line of sight from your work to operational impact. If you want your research to leave the lab and genuinely matter, we’d love to meet you.

The Role:

As our Research Engineer, you will sit at the boundary between frontier machine-learning research and shipped product. You will take ideas from the research edge, including reinforcement learning, RLHF, multi-objective policy optimisation, and LLM post-training, and turn them into capabilities that make our platforms measurably better.

This is a Research Engineer role. You will read the literature, prototype quickly, and see your work through into systems our customers depend on, while connecting that research to OD’s product vision and to what our customers actually need. As we are a UK-based organization, the expectation for the role is to align working patterns to UK office hours.

Requirements

The Right Fit:

Your responsibilities will include, but are not limited to:

• Apply and adapt machine-learning and reinforcement-learning research to OD’s product roadmap, translating research direction into shippable capability.
• Design, train, and evaluate models using reinforcement learning, RLHF, and multi-objective policy optimization, balancing competing objectives such as accuracy, safety, latency, and cost.
• Work on LLM post-training: fine-tuning, alignment, reward modelling, and rigorous evaluation.
• Prototype fast, then work with the engineering teams to harden what works into production.
• Define how frontier models can be evaluated and how decision-making can be audited.
• Engage directly with customers and stakeholders, explaining technical approaches to non-specialists and feeding real-world needs back into the research agenda.
• Help shape OD’s research and product vision, bringing a clear point of view on where the field is heading and what OD should build next.

Requirements:

What you can bring to Oxford Dynamics

You will operate as both a researcher and an engineer: reading the frontier, building real systems, and acting as a credible technical voice with customers. A strong focus on turning research into product impact, with the judgement to know what is worth building.

Qualifications, experience, and skills

• A PhD in AI, machine learning, or a closely related field, or holding a current postdoctoral research position in Machine Learning.
• Strong grounding in Machine Learning and reinforcement learning, including RLHF.
• Hands-on experience with multi-objective policy optimisation.
• Solid knowledge of transformer architectures and LLM post-training (fine-tuning, alignment, reward modelling).
• Publications at top-tier AI conferences such as ICML, ICLR, NeurIPS, CVPR, etc.
• Experience using HPCs and CUDA for training large-scale models.
• The ability to translate research into a product vision and carry it through to delivery.
• Nice to have: computer vision experience, open-source contributions, or applied research that shipped into a product.

Soft skills

• Commercial thinking: an instinct for connecting research effort to product value and customer impact, rather than research for its own sake.
• Communication and client-facing skills: able to explain complex ideas clearly to both technical and non-technical audiences, including customers.
• Calm, judgement-led decision making, and comfort operating in ambiguity with fast-moving priorities.

Benefits

Oxford Dynamics is committed to creating an inclusive team experience for all. Regardless of race, gender, religion, sexual orientation, age, disability, or parental status, we believe our work is at its best when everyone feels free to be their authentic self.