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- Tasks: Design and optimise advanced generative AI systems for real-time 3D rendering.
- Company: Join a cutting-edge tech company focused on AI and graphics innovation.
- Benefits: Attractive salary, remote/hybrid work options, and opportunities for professional growth.
- Other info: Collaborative environment with exciting challenges and career advancement potential.
- Why this job: Be at the forefront of generative AI and 3D technology, making a real impact.
- Qualifications: Experience in deep learning, neural networks, and modern ML frameworks required.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Machine Learning Engineer – Generative AI (3D & Real-Time Rendering) to join our onsite team in London. In this role, you will design, implement, and optimize advanced generative AI systems for real-time photorealistic rendering and 3D applications. You will work at the intersection of deep learning and computer graphics, collaborating closely with rendering and engine teams to integrate cutting-edge AI into production-grade pipelines.
You will tackle challenging problems such as low-latency inference, controllable generation, and deploying generative models within real-time rendering systems.
- D. in Computer Science, Mathematics, Electrical Engineering, or a related field; Master’s degree with 2+ years of relevant industry experience; Bachelor’s degree with 4+ years of relevant industry experience.
- Strong expertise in deep learning, neural networks, and generative models (diffusion, GANs, transformers).
- Hands-on experience with modern ML frameworks.
- Advanced programming skills in Python.
- Solid understanding of model training, evaluation, and scaling.
- Experience with 3D vision, neural rendering, or photorealistic rendering pipelines.
- Familiarity with rendering engines (e.g., Unreal Engine, Unity) or custom 3D engines.
- Experience with multimodal and foundation models (e.g., text-to-3D, video generation).
- GPU programming experience (CUDA, Triton, or similar).
- Experience integrating ML models into production pipelines.
Develop and optimize state-of-the-art generative AI systems (diffusion, transformer-based models) for real-time photorealistic rendering and 3D applications. Design pipelines for controllable, high-fidelity, low-latency generation within rendering systems. Collaborate with graphics and rendering teams to integrate AI models into real-time engines and production pipelines. Prototype, benchmark, and productionize algorithms for photorealistic 2D/3D content generation. Advance techniques in neural rendering, scene generation, and AI-driven photorealism. Improve model efficiency, scalability, and deployment performance.
If you are passionate about generative AI, real-time photorealistic rendering, and 3D systems, and want to help build the next generation of AI-driven graphics pipelines, we’d love to hear from you.
ML Engineer - REMOTE/HYBRID in London employer: LIT8
Contact Detail:
LIT8 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - REMOTE/HYBRID in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to generative AI and real-time rendering. We want to see what you can do, so make it easy for us to be impressed!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We love candidates who can think on their feet, so practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals who want to join our team and help shape the future of AI-driven graphics.
We think you need these skills to ace ML Engineer - REMOTE/HYBRID in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with deep learning, neural networks, and generative models. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about generative AI and real-time rendering. We love seeing enthusiasm, so let your personality come through while keeping it professional.
Showcase Your Projects: If you've worked on any cool projects related to 3D vision or photorealistic rendering, make sure to mention them! We appreciate hands-on experience, especially if you’ve contributed to open-source projects or collaborated with research labs.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at LIT8
✨Know Your Stuff
Make sure you brush up on your deep learning, neural networks, and generative models. Be ready to discuss specific projects you've worked on, especially those involving diffusion, GANs, or transformers. This is your chance to show off your expertise!
✨Showcase Your Experience
Prepare to talk about your hands-on experience with modern ML frameworks and any relevant programming skills in Python. If you've integrated ML models into production pipelines or contributed to open-source projects, make sure to highlight these experiences during the interview.
✨Familiarity with Tools
Since the role involves working with rendering engines like Unreal Engine or Unity, it’s a good idea to familiarise yourself with these tools beforehand. Being able to discuss how you’ve used them in past projects will definitely give you an edge.
✨Problem-Solving Mindset
Be prepared to tackle some challenging problems during the interview. Think about how you would approach low-latency inference or controllable generation in real-time rendering systems. Showing your problem-solving skills can really impress the interviewers!