SENIOR MACHINE LEARNING DEVELOPER

1 Week ago • All levels

About the job

Job description

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


Job requirements

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@framestore.com 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!

About The Company

Framestore combines talent and technology to reframe the possible in film, content, advertising and immersive experiences.

Founded in 1986, Framestore is now a global company of over 3,000 people across eight locations. We create pixel-perfect images for blockbuster films and TV, iconic advertising campaigns and innovative immersive projects.

Our portfolio of work is underpinned by an industry-leading expertise in VFX and has resulted in a multitude of awards including Oscars and BAFTAs as well as a record number of Cannes Lions awards, which all cement our position at the forefront of innovation.

We have studios in London, Montreal, Vancouver, New York, Los Angeles, Chicago, Mumbai, Melbourne. Visit our website for current vacancies in film, advertising and immersive: https://www.framestore.com/careers 

England, United Kingdom (On-Site)

Victoria, Australia (On-Site)

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