Artificial Intelligence Researcher Engineer

AI Research Engineer (PhD)

MITO AI · United Kingdom (Remote) · Open to Europe

AI Research Engineer (PhD) — Generative & Multimodal AI for Creative Production

Location: Remote (UK) — open to Europe, especially Madrid | Experience Level: Mid-Senior (PhD graduate or experienced Research Engineer)

About MITO AI

MITO AI is a collaborative, AI-native platform reinventing how films, commercials, and music videos are made. We are building the operating system for a $300B+ global video production industry shifting to AI-native workflows.

MITO brings together state-of-the-art AI models for image, video, and audio with professional-grade agentic editing tools in a multiplayer, browser-based canvas. Director, MITO's AI agent, helps brands, agencies, and creators plan, generate, organise, and refine work across a whole project.

MITO was founded by Iñaki Berenguer (MIT, PhD Cambridge, 5x founder — Pixable acquired by SingTel, CoverWallet $300M exit, iPronics $50M raised), Danny Saltaren (product designer at 2 unicorns, National Design Award), and Arantxa Barcia (award-winning filmmaker).

We are backed by Lightspeed Venture Partners, Bessemer Venture Partners, and other investors including Kibo Ventures, Kfund, Sequoia and a16z scouts, LifeX, Everywhere, 5 unicorn founders, and execs from GitHub and Roblox.

The Role:

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.

Key Responsibilities:

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.

About You:

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).

Compensation & Perks:

• Work on hard AI problems that arise from real creative production — not synthetic benchmarks.
• Take ideas from experiment through to implementation and see how they perform with professional filmmakers using the product.
• Broad exposure to generative and multimodal models, methods, and tools at the frontier.
• Substantial ownership from day one — this is the first research hire, and what you build shapes the function.
• Competitive salary and equity.
• Remote from the UK or Europe — we have a strong presence in Madrid and welcome candidates based there.

How to Apply:

Send us your CV alongside examples of your research and engineering work: publications, research projects, open-source contributions, prototypes, or deployed systems. We want to understand what you have built and how you think — not just where you have worked.

MITO AI — www.mito.ai