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

Apply Now

Machine Learning Engineer

Alexander Daniels Global
Oxford
3 days ago
Create job alert

Machine Learning Engineer – Onsite in Oxford

Location: Oxford, UK


Employment Type: Full-time, Onsite

Are you passionate about applying cutting-edge machine learning to real-world challenges? This is an opportunity to work at the intersection of AI and advanced manufacturing, helping to optimize processes and material composition through innovative solutions.


What You’ll Do

  • Design, develop, and validate novel machine learning models to optimize manufacturing processes and material composition.
  • Collaborate closely with process engineers, material scientists, and domain experts to identify and engineer meaningful features.
  • Develop internal machine learning platforms to enable adoption and application of validated models.
  • Work as part of a fast-paced, agile development team, identifying and prioritizing opportunities to deliver new capabilities.
  • Build and maintain robust MLOps pipelines for scalable, reproducible, and automated model development, deployment, and monitoring.
  • Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices and model governance.


Essential Skills

  • Master’s degree in Machine Learning, Mathematics, or Statistics.
  • Strong understanding of probabilistic model development.
  • Experience with Bayesian modelling.
  • Solid grasp of software design principles and best practices.
  • Proficiency in at least one object-oriented programming language.
  • Familiarity with cloud platforms (Azure, AWS, GCP) and infrastructure-as-code tools (e.g., Terraform).


Why Apply?

You’ll join a team working on high-impact projects that combine advanced materials science with machine learning innovation. Expect a collaborative environment, opportunities for growth, and the chance to make a tangible difference in next-generation manufacturing.

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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 Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.