Machine Learning Engineer Consultant

Electus Recruitment Solutions
Cambridge
2 weeks ago
Applications closed

Related Jobs

View all jobs

On-site Machine Learning Engineer Consultant — Cambridge

Graduate Machine Learning (ML) Engineer – 29348

Senior Staff Data Engineer

Senior Staff Data Engineer

Junior Data Consultant - Grow into Data Engineer/Analyst

Senior Consultant - AI & Data, Financial Services, Data Platforms, Data Engineer, BCM, Edinburgh

Machine Learning Engineer Consultant

Location: Cambridge, England, United Kingdom


Contract: Permanent


Salary: Competitive + Excellent Benefits


Job Description

Electus Recruitment is seeking a Machine Learning Engineer Consultant to join a dynamic SME that is part of a larger group of companies poised for significant growth. As a Machine Learning Engineer Consultant, you will contribute to innovative projects that protect the UK from emerging threats.


Key Responsibilities

  • Conduct in-depth research into state-of-the-art machine learning techniques and related emerging technologies.
  • Design, develop and implement machine learning models for a variety of tasks, from proof-of-concept to working prototypes.
  • Understand the underlying algorithms, mathematical concepts and workings of machine learning techniques.
  • Collaborate with a multi-disciplinary team of experts to solve complex challenges.
  • Communicate solutions to technical and non-technical stakeholders.

Requirements

  • Strong technical skills and proven track record in machine learning research, with a focus on deep learning techniques and neural network architectures.
  • Experience with machine learning libraries and frameworks such as PyTorch, TensorFlow and Keras; data manipulation libraries such as Pandas and NumPy; and MLOPs tools such as Docker.
  • Experience with emerging machine learning technologies such as RL, XAI and Generative AI including LLMs.
  • Strong coding proficiency in Python.
  • An enquiring mind and a passion for problem-solving.
  • Post‑Graduate Degree and research experience or a PhD in a relevant field such as Physics, Mathematics, Computer Science or Engineering.
  • Ability to obtain and maintain UK security clearance.

This is an on-site role. A flexible working policy exists however the applicant is expected to be on‑site for the majority of the time.


"Due to the nature of work undertaken by our client, incumbents of these positions are required to undergo pre‑employment screening and must be able to satisfy clearance criteria for UK Security Vetting".


Benefits

  • Competitive salary and benefits package.
  • Opportunity to work on challenging and rewarding projects.
  • Collaborative and supportive work environment.
  • Access to state-of-the-art facilities and resources.
  • Opportunities for professional development and growth.
  • Generous pension scheme.
  • Private medical insurance.
  • Employee assistance program.
  • Company‑sponsored social events.
  • Comprehensive relocation package available, if applicable.
  • Join a company that is committed to growth and innovation. They are a dynamic SME with ambitious plans to double their size over the next five years. As part of our client's team, you can contribute to their success and be part of something truly exciting.

To apply please send us your CV highlighting your relevant experience.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.