Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Data Careers Ltd
Bristol
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.