National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer - Generative AI

Qubit Analytics
London
4 days ago
Create job alert

Company Description

We are a startup building next-generation real-time image-to-image transformation models, with a special focus on 3D applications and rendering engine integration. Leveraging the latest in GANs, diffusion models, and large-scale deep learning, our research-driven team values autonomy, creativity, and technical excellence. Join us to help shape the future of real-time 2D/3D generative AI in a highly collaborative and innovative environment.


Role Description

We are seeking a Machine Learning Engineer – Generative AI to join our onsite team in London. In this role, you will design, implement, and optimize advanced generative AI models for real-time image and 3D applications, collaborating closely with experts in computer graphics and rendering. You’ll have the opportunity to work on some of the most technically challenging problems at the intersection of deep learning and real-time 3D systems.


Minimum Qualifications

  • Ph.D. in Computer Science, Mathematics, Electrical Engineering, or a related field; or Master’s degree with 2+ years of relevant industry experience; or Bachelor’s degree with 4+ years of relevant industry experience.
  • Strong expertise in deep learning, neural networks, and generative models (GANs, diffusion models).
  • Practical experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow).
  • Advanced programming skills in Python.
  • Strong problem-solving, analytical, and communication skills.
  • Demonstrated ability to work effectively in multidisciplinary, fast-paced, research-driven teams.


Preferred Qualifications

  • Experience with 3D vision, computer graphics, or real-time rendering engines (e.g., Unreal Engine, Unity, custom 3D engines).
  • Proven track record of publications at top-tier conferences (e.g., NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV).
  • Experience with GPU programming (CUDA) and model optimization for real-time inference (e.g., quantization, pruning, ONNX, TensorRT, custom CUDA kernels).
  • Background in scalable algorithm design for real-time or interactive applications.
  • Experience integrating machine learning models with complex production pipelines, including 3D graphics or AR/VR systems.
  • Contributions to open-source research codebases or prior collaboration with academic/industry research labs.


Key Responsibilities

  • Develop and optimize state-of-the-art generative models (GANs, diffusion models) for real-time image-to-image and 3D/graphics tasks.
  • Collaborate with 3D graphics and rendering teams to integrate AI models into interactive applications and pipelines.
  • Prototype, benchmark, and productionize new algorithms that advance real-time generative AI for both 2D and 3D content.
  • Research and experiment with emerging techniques to keep our technology at the cutting edge.
  • Work cross-functionally to align technical solutions with business goals and product needs.


What We Offer

  • The opportunity to work at the intersection of deep learning, 3D vision, and real-time graphics.
  • A dynamic, research-driven environment where your work directly impacts next-gen 3D/AI products.
  • Access to world-class compute resources and support for continued research and publication.
  • A culture that values technical excellence, creativity, and personal growth.
  • Competitive salary.


If you are passionate about generative AI, love working with 3D graphics and rendering technology, and want to be part of a world-class team building the future of real-time AI, we’d love to hear from you!

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

National AI Awards 2025

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.

Top 10 Mistakes Candidates Make When Applying for AI Jobs—And How to Avoid Them

Avoid the biggest pitfalls when applying for artificial intelligence jobs. Discover the top 10 mistakes AI candidates make—plus expert tips and internal resources to land your dream role. Introduction The market for AI jobs in the UK is booming. From computer-vision start-ups in Cambridge to global fintechs in London searching for machine-learning engineers, demand for artificial-intelligence talent shows no sign of slowing. But while vacancies grow, so does the competition. Recruiters tell us they reject up to 75 per cent of applications before shortlisting—often for mistakes that could have been fixed in minutes. To help you stand out, we’ve analysed thousands of recent applications posted on ArtificialIntelligenceJobs.co.uk, spoken with in-house talent teams and independent recruiters, and distilled their feedback into a definitive “top mistakes” list. Below you’ll find the ten most common errors, along with actionable fixes, keyword-rich guidance and handy internal links to deeper resources on our site. Bookmark this page before you hit “Apply”—it could be the difference between the “reject” pile and a career-defining interview.

Top 10 Best UK Universities for AI Degrees (2025 Guide)

Discover the ten best UK universities for Artificial Intelligence degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right AI programme for you. Artificial Intelligence continues to transform industries—from healthcare to finance to transportation. The UK leads the way in AI research and education, with several universities consistently ranked among the world’s best for Computer Science. Below, we spotlight ten UK institutions offering strong AI-focused programmes at undergraduate or postgraduate level. While league tables shift year to year, these universities have a track record of excellence in teaching, research, and industry collaboration.

How to Write a Winning Cover Letter for AI Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for AI jobs with this proven 4-paragraph structure. Perfect for junior developers and career switchers. When applying for an AI job, your cover letter can make all the difference. For many, the process of writing a cover letter for an AI position can be daunting, especially when there are so few specific guides for tailoring it to the industry. However, a clear, effective structure combined with AI-specific language and examples can help you stand out from the competition. Whether you're a junior entering the field or a mid-career professional switching to AI, the following framework will make it easier for you to craft a compelling cover letter. In this article, we’ll take you through a proven four-paragraph structure that works and provide sample lines that you can adapt to your personal experience.