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- Tasks: Fine-tune Vision Language Models and deploy them in real-world gaming environments.
- Company: Exciting AI games startup in London with a focus on innovation.
- Benefits: Competitive salary up to £200k, equity options, and hybrid work model.
- Why this job: Join a pioneering team creating autonomous agents that revolutionise gaming interaction.
- Qualifications: Experience with Vision Language Models and video data; coding skills essential.
- Other info: Dynamic startup culture with opportunities for significant impact and growth.
The predicted salary is between 108000 - 192000 £ per year.
Spent serious time fine tuning Vision Language Models, not just reading about them?
Worked with video data, temporal context, and models that need to understand what’s happening over time, not just in a single frame?
Comfortable taking research ideas and turning them into something that actually runs in production?
The challenge: This startup is building autonomous agents that understand and interact with games the way humans do. That starts with perception. They’ve built their own proprietary model that has beaten the likes of Google and Anthropic on benchmarking. You’ll own the core VLM work that turns raw video and images into usable game understanding. This is not a pure research role and it’s not just application glue. It sits in the middle, applied R&D with real constraints. Your models will be the brain that agents rely on in live environments.
What you’ll be working on:
- Fine tuning and optimising Vision Language Models such as LLaVA, CLIP, Flamingo, Gemini or similar
- Training models on video data, not just static images
- Designing inputs that capture temporal context across multiple frames
- Balancing model quality with inference speed and cost
- Taking models all the way to deployment in a production environment
About you: You’re likely an AI Engineer or Applied Researcher who:
- Has hands on experience fine tuning Vision Language Models
- Has worked with video data and understands temporal modelling challenges
- Enjoys applied R&D and shipping code
- Can handle some MLOps to get models into production
- Thinks about inference, latency, and cost, not just accuracy
A research or academic background is helpful but not required. What matters is that you’ve actually built and deployed things.
Nice to have, not must haves:
- CUDA or low level inference optimisation
- PEFT or model compression techniques
- Experience optimising models for real time inference
Not for you if you only want to publish papers or your experience with VLMs is mostly theoretical.
Interested? If you’ve built agents that actually do things and want to take real ownership, get in touch.
Artificial Intelligence Researcher employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Researcher
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and gaming industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with Vision Language Models and any projects you've deployed. We want to see what you can do, so make it easy for potential employers to see your talent.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of temporal modelling and be ready to discuss how you’ve tackled challenges in your past projects. We want to hear about your hands-on experience and how you can contribute to our team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. We’re excited to find someone who’s ready to take ownership and make an impact in our AI games startup.
We think you need these skills to ace Artificial Intelligence Researcher
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and Vision Language Models shine through. We want to see that you've spent time fine-tuning models and not just reading about them. Share specific projects or experiences that highlight your hands-on skills!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Make sure to explain your experience with video data and temporal context in a way that's easy to understand. Remember, we want to know what you can bring to the table!
Highlight Your Deployment Experience: Since this role is all about taking research ideas into production, make sure to emphasise any experience you have with deploying models. Talk about the challenges you faced and how you overcame them. We love seeing candidates who can bridge the gap between research and real-world applications!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you're serious about joining our team at this exciting AI Games startup!
How to prepare for a job interview at MBN Solutions
✨Know Your Models Inside Out
Make sure you can discuss the Vision Language Models you've worked with in detail. Be prepared to explain how you've fine-tuned models like LLaVA or CLIP, and share specific examples of challenges you've faced with video data and temporal context.
✨Showcase Your Applied R&D Experience
This role is all about turning research into production-ready solutions. Bring examples of projects where you've taken a model from concept to deployment. Highlight your experience with MLOps and how you've balanced model quality with inference speed and cost.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Brush up on CUDA, low-level inference optimisation, and any model compression techniques you've used. Being able to talk through your thought process will show your expertise and problem-solving skills.
✨Demonstrate Your Passion for AI
Let your enthusiasm for AI and gaming shine through. Share why you're excited about building autonomous agents and how you see the future of AI in gaming. This will help you connect with the interviewers and show that you're not just looking for a job, but a chance to make an impact.
