Senior Machine Learning Engineer REMOTE UK PoC into cloud

Oxford
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer Python AWS

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer, Search & Recommendations

Senior Machine Learning Scientist

Senior Machine Learning Scientist

Senior Machine Learning Engineer – REMOTE UK or HYBRID
Python, deploying models; Guide models from proof of concept to production; overseeing the full lifecycle of machine learning models; taking models into production in cloud systems; MLOps
Are you ready to harness the power of AI and data science to impact industries as diverse as satellite communications, energy management, and healthcare?
My client is looking for a Senior Machine Learning Engineer to take on a key role in transforming concepts into cutting-edge solutions, directly shaping the future of advanced technologies. This is an opportunity to lead with your expertise and see your innovations thrive across multiple high-stakes projects. Experience of taking models from PoC into cloud systems is essential.
Why You Should Apply

  • Work at the intersection of AI, advanced mathematics, and real-world impact.
  • Lead multiple projects with direct customer interaction and influence.
  • Be a technical authority in a forward-thinking, collaborative environment.
  • Mentorship and leadership opportunities, including developing the next generation of ML engineers.
  • Flexible work arrangements with a mix of remote and office options.
  • Enhanced leave benefits, mental health support, and a generous pension.
    What You’ll Be Doing
  • Build, train, and monitor robust machine learning pipelines.
  • Lead model architecture and MLOps development across multiple platforms.
  • Collaborate with consultants, engineers, and customers on cutting-edge projects.
  • Drive model trustworthiness through confidence quantification and explainability.
  • Mentor and lead teams, fostering innovation and growth.
    About You
  • Be able to do the job as described.
  • Expertise in Python, MLOps, and cloud services.
  • Experience taking models from PoC into cloud systems
  • Comfortable managing multiple, complex projects simultaneously.
  • A technical leader who can guide both clients and team members.
  • Experience in confidence quantification and model explainability.
  • Ideally demonstrable experience in AWS or Azure
    Please apply via the link for immediate consideration

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.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.