National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer

Data Careers Ltd
Bristol
7 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer - Bioimage Data & Agentic Systems

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer - Generative AI

Machine Learning Engineer9 Month ContractLocation: Home / Bristol (3 days a week on site)Rate: £750 - £800 per day (Inside IR35)Skills: Machine Learning, Containerisation - Kubernetes, Docker, CI/CD Pipelines, SC ClearanceWe are looking to recruit a Machine Learning Engineer for leading IT Software & Solutions organisation. This is an initial 9 month contract.Due to the work valid SC Clearance is essential.You will also be required to work on client site in Bristol 3 days a week.Key Responsibilities:Set Up & Configure ML Environments: Deploy and manage ML environments using tools like Kubernetes and Docker.Automation & Workflow Optimization: Develop scripts for automation and ensure reproducibility of ML experiments.Performance Monitoring: Conduct regular model performance reviews, data audits, and troubleshoot model-related issues.Cross-functional Collaboration: Work within cross-functional teams to establish ML development best practices and secure CI/CD pipelines.Scalable, Secure Solutions: Develop robust, secure, and scalable solutions while adhering to MOD and high-assurance compliance standards.Innovative ML Development: Identify opportunities for reusable solutions to maximize return on development investments.Essential Skills:Technical & Problem-Solving Skills: Strong analytical skills for logical solution analysis and troubleshooting.ML Environment Experience: Proficient with Linux/Windows, ML frameworks (e.g., TensorFlow, PyTorch), and automation tools.Programming Proficiency: Expertise in Python, Ruby, Perl, Java, with advanced scripting skills in Bash or PowerShell.Model Monitoring & Performance Evaluation: Experience with MLflow, Prometheus, and similar tools for monitoring and logging.DevOps & Agile Awareness: Familiar with DevOps, Agile principles, CI/CD pipelines, and version control (Git).Security & Compliance: Understanding of secure code practices, threat modelling, and adherence to regulatory standards for high-assurance software.Additional Experience:Industry Background: Over 5 years in defence, aviation, or medical sectors within roles such as software, DevOps, DevSecOps, MLOps, or AI engineering.Complex Project Experience: Proven experience with software and AI development and deployment in complex, high-stakes environments.Technical Documentation: Strong skills in producing high-standard technical documentation.Desirable Skills:Data Project Development: Experience with large-scale data project implementation and solution governance.Frameworks & Infrastructure Knowledge: Familiarity with SaaS, IaaS, PaaS, SOA, APIs, microservices, and predictive analytics.Qualifications:Essential: Degree or equivalent in Software/AI, or relevant experience.Desirable: Certifications in software languages, vendor qualifications (e.g., MCITP, VCP), and Agile/SAFe qualifications

National AI Awards 2025

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 to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.