Opus Recruitment Solutions
ML / Data Engineer

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About the Company
I'm partnering with a well-funded technology company building next-generation AI products and looking for an experienced ML / Data Engineer to help shape the future of intelligent decision-making systems.
About the Role
This is an opportunity to work at the intersection of:
- Machine Learning
- Computer Vision
- Generative AI
- Large Language Models
- Production AI Engineering
The Role
You'll be responsible for developing, evaluating, and deploying machine learning models that solve complex real-world problems at scale. Working alongside a highly technical team of engineers and researchers, you'll help design intelligent systems that combine multiple AI approaches, balancing performance, reliability, and operational efficiency.
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.
Responsibilities
Key responsibilities include:
- Developing and improving machine learning and deep learning models
- Building evaluation frameworks to measure model performance
- Fine-tuning and deploying open-source AI models
- Developing production-grade AI solutions using frontier-model APIs
- Designing data-driven feedback loops to continuously improve system performance
- Collaborating with software engineers to deploy scalable ML systems
Qualifications
Required Skills
What We're Looking For
- Commercial experience building and deploying ML models
- Strong Python skills (PyTorch, NumPy, Pandas, OpenCV, SQL)
- Experience working with LLMs, GenAI, or multimodal AI systems
- Production experience integrating external AI APIs
- Understanding of model evaluation, experimentation, and optimisation
- Experience with Docker, CI/CD, and software engineering best practices


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Preferred Skills
Nice to Have
- Computer Vision experience
- Experience fine-tuning foundation models
- MLOps or platform engineering exposure
- Experience working with large-scale datasets
Pay range and compensation package
Competitive salary, bonus, and benefits package
Equal Opportunity Statement
📩 Interested in learning more? Get in touch - Narinder.Singh@opusrs.com
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