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Tenpin

Machine Learning Engineer

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Machine Learning Engineer

We are looking for a highly motivated and experienced Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and deploying machine learning models to solve complex business problems. You will collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deliver innovative solutions.

Key Responsibilities:

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.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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It 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.

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Strong

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.

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Strong

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.

  • Develop and implement machine learning algorithms and models.
  • Preprocess and analyze large datasets.
  • Evaluate model performance and iterate for improvement.
  • Deploy models into production environments.
  • Stay up-to-date with the latest advancements in machine learning and AI.
  • Document and present findings to stakeholders.

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Qualifications:

  • Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
  • Proven experience in developing and deploying machine learning models.
  • Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning).
  • Proficiency in Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience with data processing and analysis tools.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills.
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“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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Skills

Machine learning
Python
TensorFlow
PyTorch
Scikit-learn
Data processing
Data analysis
Problem-solving
Analytical skills
Communication skills
Collaboration
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