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

Apply Now

ML Data Engineer

Experis UK
Knutsford
2 weeks ago
Create job alert
Overview

Role Title: ML Data Engineer
Company: Experis UK

Role Description: We are seeking a highly capable Data & ML Engineer with strong experience in AWS-based machine learning pipelines, MLOps, and cloud-native deployment. This role focuses on building scalable data workflows, deploying ML models, and managing the full AI lifecycle in production environments.

Start Date: ASAP

End Date: End of Year (EOY)

Location: Knutsford (Hybrid)

Rate: £410 per day via Umbrella


Responsibilities

  • Build and maintain robust data pipelines and ML workflows on AWS
  • Develop and deploy machine learning models using SageMaker and MLOps tools
  • Implement CI/CD pipelines for automated testing and deployment
  • Create lightweight front-end interfaces for model interaction and visualization
  • Monitor model performance and ensure reliability in production environments
  • Collaborate with data scientists and engineers to streamline the AI lifecycle

Key Skills & Qualifications

  • AWS Data Engineering: ECS, SageMaker, cloud-native data pipelines
  • ML Engineering & MLOps: MLflow, Airflow, Docker, Kubernetes
  • CI/CD & DevOps: GitLab, Jenkins, automated deployment workflows
  • AI Lifecycle Management: Model training, deployment, monitoring
  • Front-End Development basics: HTML, Streamlit, Flask (for lightweight dashboards and interfaces)
  • Cloud Model Deployment: Experience deploying and monitoring models in AWS
  • Programming & Big Data: Python, PySpark, familiarity with big data ecosystems
  • RESTful APIs: Integration of backend services and model endpoints


#J-18808-Ljbffr

Related Jobs

View all jobs

Azure AI Data Engineer

Data Engineer

Sr. AI Data Engineer (UK Remote)

Senior AI/ML Data Engineer - 100% Remote - EMEA

Azure AI Data Engineer

Sr. AI Data Engineer (UK Remote)

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.