At a Glance
- Tasks: Develop and optimise cutting-edge generative AI systems for real-time 3D applications.
- Company: Join a fast-moving, research-driven tech company at the forefront of AI innovation.
- Benefits: Attractive salary, creative culture, and impactful work in generative AI.
- Other info: Collaborate with talented teams and stay ahead in a dynamic environment.
- Why this job: Make a real impact in the exciting world of AI-driven graphics and 3D vision.
- Qualifications: Experience in machine learning, deep learning, and programming with Python.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Machine Learning Engineer – Generative AI with the following qualifications:
- 3D 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 (diffusion, GANs, transformers).
- Hands-on experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Advanced programming skills in Python.
- Solid understanding of model training, evaluation, and scaling.
- Strong problem-solving, analytical, and communication skills.
- Ability to work effectively in multidisciplinary, fast-paced, research-driven teams.
Preferred Qualifications:
- 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).
- Knowledge of NeRFs, Gaussian splatting, or neural scene representations.
- Experience optimizing models for real-time inference (TensorRT, ONNX, quantization, distillation).
- GPU programming experience (CUDA, Triton, or similar).
- Track record of publications at top-tier venues (NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV).
- Experience integrating ML models into production pipelines (e.g., graphics, AR/VR, simulation systems).
- Contributions to open-source projects or collaboration with research labs.
Key Responsibilities:
- 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.
- Stay up to date with the latest research and rapidly experiment with emerging approaches.
- Work cross-functionally to align technical solutions with product and business goals.
What We Offer:
- The opportunity to work at the intersection of generative AI, 3D vision, and real-time photorealistic rendering.
- A fast-moving, research-driven environment with real product impact.
- A culture that values technical excellence, ownership, and creativity.
- Very attractive salary.
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.
Machine Learning Engineer - Generative AI employer: LIT8
Contact Detail:
LIT8 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Generative AI
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving generative AI and 3D rendering. This is your chance to shine and demonstrate what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Machine Learning Engineer - Generative AI
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 how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality come through.
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, so include links to your GitHub or any publications if you have them.
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. Plus, it shows you’re keen to join us!
How to prepare for a job interview at LIT8
✨Know Your Tech Inside Out
Make sure you’re well-versed in deep learning, neural networks, and generative models. Brush up on your experience with frameworks like PyTorch and TensorFlow, as well as your programming skills in Python. Be ready to discuss specific projects where you've applied these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex problems in previous roles. Think about challenges related to model training, evaluation, or scaling, and be ready to explain your thought process and the outcomes. This will demonstrate your analytical abilities and practical experience.
✨Familiarise Yourself with 3D and Rendering
If you have experience with 3D vision or rendering engines like Unreal Engine or Unity, make sure to highlight it. Discuss any relevant projects or contributions to open-source initiatives that showcase your understanding of photorealistic rendering and real-time inference optimisations.
✨Stay Current with Research Trends
Keep up with the latest advancements in generative AI and neural rendering. Mention any recent papers or techniques that excite you during the interview. This shows your passion for the field and your commitment to continuous learning, which is crucial in a fast-paced, research-driven environment.