Machine Learning Engineer (3D Gaussian Splatting & NeRF)

M-XR
London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer - London

Machine Learning Engineer/Researcher

Machine Learning Engineer/Researcher

Machine Learning Engineer

Machine Learning Engineer

Summary


M-XR is a deep tech startup with a mission to make the 3D digital world look real; whether that be the graphics in a computer game, the CGI in a movie, or a product line photoshoot. We are building a solution that empowers 3D creators and enables the creation of productions at a speed, scale and quality not found anywhere else in the industry. Over the past three years we’ve developed foundational technology capable of capturing real world objects and accurately predicting their material properties, enabling the creation of ultra-realistic production-ready digital copies.


Curiosity and creativity are at the heart of M-XR. We feel strong that asking questions and looking at problems from new perspectives across departments is key to pushing the envelope for what is possible! We are looking for skilled individuals who share this passionate curiosity, question the norm, and have the willingness to explore something brand new. If you are an engineer or developer that shares this passion about shaping the future of 3D we would love to hear from you.


Description of work to be performed


As a Machine Learning Engineer at M-XR specializing in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), you will play a pivotal role in advancing our capabilities. Your focus will be on implementing cutting-edge computer vision algorithms for NeRF/3DGS and exploring ways to enhance these technologies by integrating segmentation, language embeddings (e.g., CLIP), and other advancements in 3D machine learning.


Leveraging M-XR’s proprietary dataset—the highest-quality ultra-realistic 3D dataset of its kind—you’ll tackle innovative projects that push the boundaries of what’s possible in machine learning and 3D. Key initiatives include 3D asset relighting and extracting ultra-realistic material properties directly from NeRFs/3DGS. A core part of your role will involve adapting, implementing, and enhancing open-source research and models such as SAM, Stable Diffusion, CLIP, DINO, NeRF, and 3DGS to create solutions tailored to our unique use cases.


Your contributions will directly set new standards for realism and quality in 3D content creation, with applications in major film and game productions. This role offers an exciting opportunity to tackle complex challenges, develop groundbreaking technologies, and witness the tangible impact of your work on the future of the entertainment industry.


Ideal Candidate


•Creative and innovative thinker

•Resourceful and effective problem-solver

•Clear, articulate, and proactive communicator

•Strong user-focused mindset

  • Collaborative and supportive team player


Requirements


•Proficiency with a major industry ML framework (e.g., PyTorch, JAX, TensorFlow)

•Expertise in writing production-quality Python code

•Experience with CUDA programming

•Familiarity with Git and version control systems

•Strong understanding of computer graphics principles

•Hands-on experience with 3D Gaussian Splatting, either through contributions to open-source NeRF/3DGS repositories or solving relevant problems in the field

•Practical experience in training and fine-tuning diffusion models (a plus)

•Knowledge of C++ (an advantage)


Please ensure your CV is attached.


Best,

M-XR


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 to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.