Machine Learning Engineer

Net Talent
Edinburgh, Scotland
12 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Faculty London, United Kingdom
Hybrid

Senior Machine Learning Engineer

Faculty London, United Kingdom
Hybrid

Lead Machine Learning Engineer

Faculty London, United Kingdom
Hybrid

Principal Machine Learning Engineer

Faculty London, United Kingdom
Hybrid

Senior Machine Learning Engineer (Recommendation)

Sky Syon, London, United Kingdom

Senior Machine Learning Engineer

PhysicsX London, United Kingdom
Posted
8 May 2025 (12 months ago)
Share
Save job
Create job alert

Job Description:We are seeking a talented and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data analysis, and software development. You will be responsible for designing, developing, and deploying machine learning models to solve complex problems and improve our products.

Key Responsibilities:

  • Develop and implement machine learning algorithms and models.
  • Analyze large datasets to extract meaningful insights.
  • Collaborate with cross-functional teams to integrate machine learning solutions.
  • Optimize and maintain existing machine learning models.
  • Stay updated with the latest trends and advancements in machine learning and AI.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • Proficiency in programming languages such as Python, R, or Java.
  • Strong understanding of mathematics and statistics.
  • Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.
  • Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib).
  • Familiarity with big data technologies (e.g., Hadoop, Spark).
  • Excellent problem-solving skills and attention to detail.
  • Ability to work independently and as part of a team.

Preferred Qualifications:

  • Experience with natural language processing (NLP) techniques.
  • Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Experience with version control systems (e.g., Git).

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.

Products

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

Jobs

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

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.

🍪 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.