Senior Machine Learning Engineer

Edison Smart
London
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senor/Principal AI/ML Engineer – Biotech
Salary: £80,000 - £120,000
Location:London/Remote

A cutting-edge Biotech company are looking for a Senior/Principal AI Engineer to join their R&D team developing novel data solutions for Biotech applications like Oncology, Pathology & RNA-Seq.

Key Responsibilities:

  • Collaborate with scientists, engineers, and product teams to build and scale AI/ML models.
  • Take projects from prototype to production-ready software.
  • Create tools for training, testing, and optimizing AI/ML models.
  • Work across cloud and on-prem environments.
  • Improve code quality and development speed.

Key Skills/Experience:

  • BS/BEng in Comp Sci, Biomedical or another relevant discipline
  • Strong experience with software or algorithm development.
  • Strong Python skills
  • Experience with deep learning frameworks (TensorFlow/PyTorch.)
  • Familiarity with version control (e.g., Git).
  • Experience with Docker or other container languages
  • A passion for applying tech to solve healthcare challenges.

Non-essential skills/nice to have:

  • Experience or understanding of Neural Networks
  • Experience with Biotechnology/Bioinformatics
  • Familiarity with AWS, Kubernetes, or RESTful APIs.
  • Exposure to regulated medical software environments.

If you are interested, please don’t hesitate to apply or send your resume directly to

About Edison Smart

Edison Smart is a global provider of specialized recruitment solutions, supporting the technology industry's most innovative companies. Headquartered in the UK, we connect talent with opportunity, driving the 'Industry 4.0' revolution. With over 30 years of experience, Edison Smart partners with forward-thinking organizations to help achieve their strategic growth goals while fostering groundbreaking technological advancements.

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 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.

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.

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.