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Senior AI Engineer – Machine Learning & Computer Vision

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Senior AI Engineer – Machine Learning & Computer Vision
No Sponsorship is available | Inside IR35 Only | 6 months contract | Hybrid - west London 3 days a week travel
We’re looking for an experienced Senior AI Engineer to build and deploy cutting-edge AI solutions using Machine Learning, Computer Vision, Deep Learning, and Generative AI. Someone passionate about building scalable, high-performance AI solutions and taking models from experimentation to production.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Develop and optimise LLMs, Generative AI solutions, and AI workflows.
- Build and deploy scalable Machine Learning and Computer Vision models.
- Work with multimodal embeddings, vision-language models, and image processing.
- Implement RAG, prompt engineering, and model fine-tuning.
- Apply MLOps practices, CI/CD, model monitoring, and performance optimisation.
- Collaborate with product and cloud teams to deliver production-ready AI solutions.


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Required Skills
- Strong Python programming skills.
- Hands-on experience with PyTorch, TensorFlow, and/or Hugging Face.
- Experience in Computer Vision, Deep Learning, and multimodal AI.
- Knowledge of LLMs, RAG, Generative AI, and model fine-tuning.
- Experience deploying ML models into production and implementing MLOps practices.
📩 Interested? Apply now and be part of the next generation of AI innovation!
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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