Lead Software Engineer (Machine Learning)

Mondrian Alpha
London
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Software Engineer - MLOps Platform

Lead Software Engineer (Machine Learning)

Lead MLOps Engineer

Lead Machine Learning Engineer, Gen AI

Senior MLOPs Engineer

Lead Data Scientist

We’re looking for exceptional talent to join a high-performance team building solutions that power some of the most advanced systems in the world. Are you a world-class engineer with a passion for tackling the hardest problems in software development? If you’re a Python virtuoso or a competitive programming/maths champion (think IMO, ACM-ICPC, Putnam), this is your chance to join a team where your skills will shine. Architect and develop cutting-edge software systems to solve complex, real-world challenges. Leverage your elite programming skills to create solutions that are fast, scalable, and elegant. Dive deep into data structures, algorithms, and optimization to build performance-critical software. Influence the culture of a firm that values curiosity, collaboration, and creative problem-solving. Elite coding skills in Python (or other languages, with a willingness to specialize in Python). Academic pedigree from top-tier universities in Computer Science or related fields. A proven track record of excellence, demonstrated by achievements like competitive programming accolades (IMO, ACM-ICPC, Putnam), publication in respected journals, or industry awards. Mastery of data structures and algorithms, with the ability to tackle challenges from first principles. Experience solving complex technical problems at scale, in fields like finance, gaming, or high-tech industries. A deep understanding of distributed systems, machine learning, or low-latency computing is a plus. Take on technically challenging projects that will stretch your skills and drive innovation. A competitive compensation package that reflects the level of talent we’re seeking, including performance-based bonuses and unparalleled growth opportunities. This isn’t just another software engineering role. It’s your chance to join an elite group where your skills will be recognized, your contributions will matter, and your career will reach new heights.

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.