Software Engineer

Marylebone High Street

8 months ago

Applications closed

Related Jobs

View all jobs

Data Engineer - DV Cleared

Senior Machine Learning Engineer

Data Engineer - SC Cleared

Lead Data Engineer

SAS Data Engineer

Lead MLOps Engineer

Software Engineer | AI / HPC | London | Hybrid | up to £120K | Lucrative stock options

Are you a Software Engineer with AI and HPC experience? Do you have a background in Computer Networks & Systems? Do you have experience developing Linux PCIe Drivers? Are you looking to work on cutting edge products in AI and Machine Learning?

Then this is the role for you!

We are working with a disruptive London-based Computer Networking company who are working on the cutting edge of AI and Machine learning technology with applications for increased productivity in Data Centre’s and HPCs.

This role will specialise in developing Linux Drivers for AI/ML within High Performance Computing (HPC) and Data Centres.

Responsibilities

Collaborating with a wide team of engineers to define software architecture.
Working on the preparation and organisation of documentation, and support stakeholders' meetings.
Work on the development of Linux PCIe Drivers for AI/ML and HPC networks.
Integration of frameworks on CPU and GPU.
Work on embedded software systems for network interfaces.
Skills and experience:

High Speed Driver experience, 100g or above.
Experience working with Linux or similar, such as Debian, Red hat & Ubuntu.
Experience developing Linux PCIe Drivers.
Experience working on verification and Validation processes.
Beneficial if you already have experience with embedded systems and RDMA.
What’s in it for you?

Up to £110k DOE
Lucrative stock options.
25 days holiday + bank holidays + Xmas/New Years Shutdown.
Hybrid working.
Private Healthcare & Life Assurance.
Relocation assistance.
Visa sponsorship provided

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Feb 3, 2026

Jobs

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Jan 29, 2026

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

Jan 24, 2026

Education

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.