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HelloKindred

ML Engineer

Posted 2 Days Ago
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Hybrid
London, England, GBR
Entry level
Hybrid
London, England, GBR
Entry level
Design, train, optimize, and deploy machine learning models for personalization, including recommendation engines, ranking, segmentation, and content analysis. Build scalable data pipelines, manage production model performance, lead A/B testing and offline experimentation, and evaluate emerging machine learning research. Collaborate with multidisciplinary teams to align technical initiatives with business and user needs.
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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 set up: 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.

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.

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.

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