Senior Machine Learning Developer

Framestore
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer, Search & Recommendations

Senior Machine Learning Engineer (MLOps)

Senior Machine Learning Engineer (AI Platform)

Senior Machine Learning Engineer (AI Platform)

As an Oscar-Award winning (Sci-Tech) team, innovation is at the heart of what we do as a company, be this developing new techniques, new ideas or creative new ways to tell our clients’ stories.

Underpinning all of this is a long tradition of research, technology and development - from engineering our bespoke software solutions to gaining early access to bleeding-edge technology and forging vibrant partnerships with leading academic and scientific institutions.

Who We Are

Framestore combines talent and technology to bring life to everything we create, whether in film, TV, advertising or immersive experiences. Driven by creativity and inspired by the future, we set out every day to reframe the possible.

The Role

We are looking for an experienced developer to join our growing Machine Learning technology team, leveraging the latest research and technology in this rapidly changing area to push the boundaries of what is possible in visual storytelling.

Your main focus in this role will be the research and development of cutting-edge machine learning algorithms and their design, development and implementations as toolsets in VFX production. You’ll work alongside our team of world-class software engineers, R&D tech leads, artists and production team in a fast-paced production environment to shape the future of our machine learning tools.

You’ll also be:

A key figure in discussions that concern strategic development at Framestore by keeping up to date on developments in ML

Mentoring other ML developers via code reviews, inclusive planning processes and technical design reviews

Helping the team ensure strong best practices around agile processes, coding standards and software design

Core Experience

Demonstrable experience of Software Engineering or other production-related work in a media production/game development company or similar industry

Experience with deep learning frameworks such as PyTorch or TensorFlow

Strong knowledge of linear algebra, statistics and optimisation

Demonstrable experience with team and workflow management - including mentoring and code reviews

Desirable Experience

Familiarity with Agile/Scrum methodologies

Experience of the use of source control systems, revision management and maintenance

A degree in Computer Science, Computer Engineering, Applied Mathematics, Statistics, Machine Learning or other related fields

Work Arrangements

At Framestore, we offer a flexible work arrangement where employees have the option to split their work time between home and office. The ML team have two weekly project days on Mondays and Thursdays where office attendance is mandatory so candidates should be able to commute easily when necessary. 

Application Process

To apply, please complete the linked application form above or if you are unable to use that link you can submit your resume to recruiters@ with the subject line: [Senior Machine Learning Developer - London].

Here is a short video of what it's like to work as part of our amazing Framestore Technology team!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.