Software Engineer (Junior)

Plymouth
9 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer - AI MLOps Oxford, England, United Kingdom

Software Engineer III- Data Engineer, Java/Python

Software Engineer: Statistics and Machine Learning (C++)

Software Engineer: Statistics and Machine Learning (C++)

Software Engineer: Statistics and Machine Learning (C++)

Software Engineer (AI & Machine Learning Focus)

Software Engineer C++ OR Python (Core Developer)
Offering excellent opportunities for further development and progression.
The company is growing their work focused on marine autonomy and machine learning, and need a software engineer to help us make this a reality. As a software engineer, you will be responsible for designing, developing, testing and prototyping various embedded control applications. You will also be required to maintain existing software products and libraries, as well as write technical documents.
In order to be successful in this role, you will have strong skills in C++ developing with Python being an advantage. You will also need a willingness to continue to develop your skillset through mentoring and online courses.
The successful candidate will be required to have strong oral, written, and interpersonal communication skills and the ability to work in a team environment. We are looking for someone who is detail-oriented and organised and can handle a variety of tasks in an efficient manner. You must also have experience or understand the concepts of the agile development cycle as well as standard quality assurance standards.
This role will offer you a flat organisational structure with engineers owning their respective systems, and the opportunity to remain involved in a system from its creation all the way through to sea-trials and sign-off.
The role may require you to be security cleared up to basic SC level as such you will need to be a UK national to be eligible to apply

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.

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.

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.

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.