HelloKindred
ML Engineer

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Company Description
Who is HelloKindred?
HelloKindred are specialists in staffing marketing, creative, and technology roles, offering a range of talent solutions that can be delivered on-site, remotely, or hybrid.
Our vision is to make work accessible and people’s lives better. We do this by disrupting traditional employment barriers – connecting ambitious talent to flexible opportunities with trusted brands.
Job Description
Anticipated Contract End Date/Length: October 19, 2029 / Contract through October 19, 2029
Work Setup: Hybrid (2 days per week in office)
Clearance Required: BPSS
Our client in the Information Technology and Services industry is looking for a ML Engineer to design, develop, optimise, and deploy machine learning models focused on user personalisation. The role will support recommendation engines, ranking algorithms, user segmentation, and content analysis, while building scalable data pipelines and collaborating with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
What you will do:
- Design, train, and optimise machine learning models focused on user personalisation, including recommendation engines, ranking algorithms, user segmentation, and content analysis.
- Construct and maintain robust, scalable data pipelines for feature engineering and model training using structured and unstructured large-scale datasets.
- Deploy and supervise machine learning models in production environments, ensuring high availability, optimal performance, and continued relevance.
- Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
- Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
- Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.
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.
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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.
Qualifications
- Bring strong experience developing and optimising machine learning models for user personalisation.
- Apply expertise across recommendation engines, ranking algorithms, user segmentation, and content analysis.
- Possess experience constructing and maintaining scalable data pipelines for feature engineering and model training.
- Have experience working with both structured and unstructured large-scale datasets.
- Demonstrate experience deploying and supervising machine learning models in production environments.
- Bring a strong understanding of A/B testing and offline experimentation for evaluating model efficacy and driving continuous improvement.
- Apply knowledge of machine learning, deep learning, and personalisation research to identify opportunities for innovation.
- Collaborate effectively with multidisciplinary teams and align technical initiatives with business objectives and user needs.


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Additional Information
- Candidates must be legally authorized to live and work in the country where the position is based, without requiring employer sponsorship.
- HelloKindred is committed to fair, transparent, and inclusive hiring practices. We assess candidates based on skills, experience, and role-related requirements.
- We appreciate your interest in this opportunity. While we review every application carefully, only candidates selected for an interview will be contacted.
- HelloKindred is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, colour, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic under applicable law.
Department: Tech Staffing
Anticipated Hours per Week: 37.5
Work Setup: Hybrid
Compensation: up to GBP 537 - daily
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