Machine Learning & Data Scientist

Reading
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Data Scientist

Data Scientist

Junior / Graduate Data Scientist

Machine Learning Manager

Data Scientist

Job Title: Machine Learning & Data Scientist

Location: Reading, UK (Hybrid)

Salary: Up to £80,000 per annum

About Us: We are dedicated to enhancing the global growth and resilience of renewable energy transmission by delivering intelligent, autonomous robotic monitoring solutions for high-voltage assets. Our mission focuses on supporting power transmission operators worldwide with advanced technologies.

Role Overview: We are seeking a Machine Learning & Data Scientist to join our dynamic team. The ideal candidate will have experience in developing multimodal models and a background in condition monitoring, particularly concerning high-voltage assets. This role offers the opportunity to contribute significantly to the development of AI-powered analytics for autonomous robotic systems.

Key Responsibilities:

Develop and implement machine learning algorithms, focusing on multimodal data integration.
Design and deploy predictive models for condition monitoring of high-voltage assets.
Collaborate with cross-functional teams to integrate AI solutions into autonomous robotic systems.
Analyze large datasets to extract meaningful insights and inform decision-making.
Stay abreast of the latest developments in machine learning and apply them to ongoing projects.Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field.
Proven experience in developing and deploying multimodal machine learning models.
Familiarity with condition monitoring techniques, especially in the context of high-voltage assets.
Proficiency in programming languages such as Python or C++.
Experience with data visualization tools and techniques.
Strong problem-solving skills and the ability to work collaboratively in a team environment.Desirable Skills:

Experience with autonomous robotic systems.
Knowledge of the energy transmission sector.
Familiarity with ISO 27001 standards.

Benefits:

Share option plan

All full-time employees become eligible for participation in the share option plan after 6 months of employment. The share option plan gives employees a real opportunity to share in the success of the business in the longer term, over and above the sense of only working for a monthly wage.

Flexible hybrid working

We allow employees to work in the lab or remote with line-manager approval, as best suits the nature of their role and the work they are performing at any time (i.e. physical aspects of mechanical engineering, such as prototype production, tend to be heavily biased towards in-lab, whereas CAD design work, software architecture design, and sales activities are less so).

Paid vacation time

We offer twenty-five days paid holiday, and 'unlimited' additional unpaid leave. This allows our employees to manage a healthy work life balance, contributing to happy, productive, and engaged employees. Managers retain the right of approval for all holidays (paid and unpaid), allowing us to ensure work capacity in times of peak demand or tight deadlines. Our culture and hiring standards help us identify people that are unlikely to abuse the holiday policy, and, in the rare cases where that might occur we have the opportunity to use performance management to correct any potential abuse or part company with the abusive employee.

Contributory Pension

We provide a workplace pension scheme to help our employees save for their retirement. Employees can elect to make a salary sacrifice to benefit from pension tax incentives, and the business complements the employee contribution with a contribution from the company.

Cycle to work scheme

A cycle to work scheme is a great incentive for employees, allowing them to purchase a bike for work-related commuting as well as non-work leisure activities. The monetary savings for the employee can be significant, and the health benefits can increase employee physical and psychological health which improves work and retention. Furthermore, it contributes to lowering our carbon footprint and even creates employer's national insurance cost savings.

How to apply?

Please send a CV to (url removed)

People Source Consulting Ltd is acting as an Employment Agency in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.