Founding Machine Learning Engineer | London | Audio/Vision

SoCode Limited
London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer PyTorch LLM

Machine Learning Engineer PyTorch LLM

Research Fellow in Machine Learning for Neutrino Physics

Data Scientist

Data Scientist

Lead Data Scientist

What We Can Offer YouThe opportunity to join a startup in its foundational stages, where your input will directly shape the product roadmap.A steep learning curve with opportunities to learn from industry leaders and delve deep into product development.Be a part of an exciting greenfield project with immense growth potential.Role OverviewAs a founding Development Engineer, you will join a small but steadily growing R&D team at the forefront of product innovation. You will be responsible for building and implementing machine learning and computer vision software solutions, aligned to the product roadmap and any future pivots. This is an opportunity to take ownership of the technical direction while seeking mentorship from experienced professionals to continuously challenge and expand your learning.Responsibilities:Design and implement scalable, high-performance software.Collaborate with cross-functional teams to define and deliver new features.Optimise code for performance, reliability, and maintainability.Contribute to a culture of continuous improvement and innovation.What We’re Looking For:A strong academic background, ideally with top marks in Computer Science or a related STEM subject, and a passion for software development.2–5 years of commercial experience in a software development role, building AI-focused products in Machine Learning or Computer Vision, ideally within the Video and/or Audio domains.Familiarity with modern fr...

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.