R&D Engineers - All Levels ILM London

Industrial Light & Magic
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst Consultant - R&D

Device Simulation and Design Engineer

Research Software Engineer

Senior Machine Learning Engineer

Embedded Software Engineer

Senior Machine Learning Developer - Stevenage

Job Summary:

Position Summary


We are seeking talented R&D engineers at all levels to join our innovative and collaborative R&D team.


Who We Are:

Industrial Light & Magic, founded in 1975 by George Lucas, has created some of the most iconic moments in motion picture history. From Star Wars to Jurassic Park, Pirates of the Caribbean, Transformers, The Avengers, theme park rides and interactive experiences, ILM continues to expand the possibilities of what visual entertainment can be.

ILM’s Research and Development (R&D) group develops the ground-breaking technology that empowers our artists to create dazzling visuals. ILM’s innovations have won 34 Scientific and Technical Academy Awards. Today, we are 70+ visually-minded software engineers, working side-by-side with over a thousand digital artists in a fast-paced, intensely collaborative, creative film production environment, across studios in San Francisco, Vancouver, London, Sydney, and Mumbai.

At ILM, a good idea is a good idea, regardless of where it comes from! Do you thrive in a creative environment? Do you enjoy sharing knowledge and learning from others? If you love art, technology, and movies, then this might be the role you’re looking for!


Responsibilities include:

Developing tools and production techniques across all areas of visual effects and feature animation production.

Developing innovative algorithms, crafting artist-friendly user interfaces, optimising data management processes, and building special purpose content creation tools that handle large-scale photo-realistic visual effects production. 

Working with engineers across all ILM’s studios, splitting time between long-term software development projects and day-to-day artist support, consultation, and problem-solving.

Collaborating with commercial software vendors in developing and deploying the next generation of machine-learning-based tools wherever applicable.

Occasional shot work alongside artists

Image processing, compositing, and rotoscoping, including depth estimation, image segmentation, generative in-painting, and plate relighting.

Simulating natural phenomena, rigid-body destruction, crowds and procedural animation.

Lighting, texturing, look-development, and layered material definition.

Modeling, rigging, and animation of bodies and faces, including soft-body dynamic simulation of cloth, hair, and flesh.

Tools, structures, and pipeline systems that define how artists assemble and manage massively complex 3D scenes, and user interfaces for authoring, validating, publishing, and tracking 3D and 2D data as it moves through a network of automated batch processes.

Senior level roles will have people and\or project leadership responsibilities.

We welcome engineers with a passion for applying the latest machine learning technology to these challenges and more!

What to Bring:

Proven experience relevant to the level of role with professional software development and/or VFX production.

Proficiency in C++ and Python on Linux.

Knowledge of and/or a desire to expand your expertise in the principles of visual effects, potentially with a specialty such as modeling, animation, lighting, rendering, image processing, etc.

Experience with Maya, Houdini, Katana, Mari or other commercial software applications is preferred, otherwise the ability to demonstrate a proactive learning attitude to support knowledge and\or skills ence with machine learning techniques, processes, and toolsets.

Working knowledge of standard data formats: OpenEXR, OpenVDB, Alembic, USD, etc. 

A passion for designing artist-friendly interfaces using GUI toolkits: Qt, PySide, QML, etc. You don’t need to be a professional UX designer, but you should have a keen sense for how creative people use technology to work together in production.

An understanding of software development principles: object-oriented design, test-driven development, source code management, build and release processes. 

Extensive experience developing in at least one of the above listed niches. 

Applicable to Senior level positions: Leadership and mentoring experience is required.

Education / Experience:

BS and/or advanced degree in computer science or related field, or equivalent level of experience.

This role is Hybrid, which means the employee will be required to work a minimum of 2 days on-site per week at a Company designated location, and occasionally from home.


JoinILM

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.