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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Artificial Intelligence Researcher Engineer - **Company:** MITO AI - **Location:** Oxford, UK (Remote available) - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, TypeScript, Pytorch, Machine Learning Operations, Software Version Control - **Published:** September 24, 2026 - **Apply:** https://www.collegerecruiter.com/job/2902050217-artificial-intelligence-researcher-engineer ## About the Role IMPORTANT: This is not a role for ML engineers who have run training jobs but haven't done research. We need someone who can design experiments, interpret results carefully, and know the difference between a result that holds and one that doesn't. * Research foundation: A PhD in machine learning, artificial intelligence, computer vision, or a related field. * Engineering depth: Strong ability to turn research ideas into working, scalable systems - not just notebooks. * Experimental rigour: Evaluation design, ablations, error analysis, and careful interpretation of results are how you work, not afterthoughts. * Production experience: You have shipped and operated AI or machine learning systems in production, not just in research settings. * Technical fluency: Python and at least one of PyTorch or JAX. Good software engineering practices: testing, version control, reproducibility, maintainable code. * Independence: You can drive a project from problem definition to deployed improvement, and you know when to ask for input. The role spans several areas. We do not expect depth in all of them - but you should bring real depth in at least one, and the curiosity and ability to learn the others: video generation, video understanding, or computer vision; diffusion models, flow-matching models, or multimodal transformers; multimodal representation learning, cross-modal retrieval, or personalisation in generative AI systems; evaluating image, video, and audio outputs where quality depends on human judgement; fine-tuning, post-training, or training generative, multimodal, reward, or evaluation models; distributed training, model serving, or inference optimisation. Also useful: experience building AI products or creative tools for filmmakers or designers; Java or TypeScript (our product stack). ## Description This is MITO's first AI Research Engineer hire. You will have responsibility for both the idea and its implementation - investigating recent advances in AI, designing rigorous experiments, developing new approaches when existing methods fall short, and building the systems that bring successful results into the product. The role combines real research with real engineering. You will prototype new approaches, evaluate whether they work, and ship the ones that do. You will work closely with MITO's VP of AI with meaningful autonomy and genuine input into what we work on - shaped by product priorities and by what we learn from the filmmakers and creators using MITO every day. We welcome candidates at different career stages, from recent PhD graduates with strong engineering skills to experienced Research Engineers. We will adjust the scope and level of the role to match the right person., Research & Engineering Ownership * Own research and engineering projects that improve the quality, capability, control, and reliability of MITO's AI systems. * Develop and test new approaches, then turn successful results into working product improvements. * Assess new models and methods against real creative needs and integrate the ones that provide clear value. Evaluation & Infrastructure * Design experiments and benchmarks to understand system behaviour - and build the evaluation infrastructure, datasets, tests, and human-review processes that make AI behaviour measurable and failures reproducible. * Use product behaviour, user feedback, and recurring failures to identify the most impactful areas for improvement. * Build data and experimentation systems that support faster, more reliable iteration. Cross-Functional Collaboration * Work with engineers, product teams, filmmakers, designers, and users to define success and deliver improvements. * Communicate results clearly - in writing and in conversation - so that research findings translate into product decisions. ## Related Videos - [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) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [Focoos AI: Building the Future of Computer Vision](https://www.wearedevelopers.com/videos/1659-focoos-ai-building-the-future-of-computer-vision) - [Are We All Prompt Engineers? How AI Changed What It Means to Build Software](https://www.wearedevelopers.com/videos/1980-are-we-all-prompt-engineers-how-ai-changed-what-it-means-to-build-software) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [The AI-Ready Stack: Rethinking the Engineering Org of the Future](https://www.wearedevelopers.com/videos/1706-the-ai-ready-stack-rethinking-the-engineering-org-of-the-future) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)