National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineer (ML) - Gloucester - National Security

All The Top Bananas
Gloucester
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Location(s): UK, Europe & Africa : UK : GloucesterBAE Systems Digital Intelligence is home to 4,500 digital, cyber and intelligence experts. We work collaboratively across 10 countries to collect, connect and understand complex data, so that governments, nation states, armed forces and commercial businesses can unlock digital advantage in the most demanding environments.We are looking for experienced Data Engineers to join our team following continuous growth and success in the UK Government sector.Our people are what differentiates us, they are resourceful, innovative and dedicated. We have a mix of generalists and specialists and recognise that this diversity contributes to our success. We recognise the benefits of forming teams from a mix of disciplines, which allows us to come up with cutting edge, high quality solutions.Our breadth of work across the Public Sector provides diverse opportunities for our people to develop their careers in new areas of expertise and with new clients. Our projects are spread across the Data Science lifecycle from delivering Research and Proof of Concept models, to building and delivering operational solutions.Machine Learning (ML) Engineers are responsible for designing, implementing, deploying, and maintaining artificial intelligence (AI) systems. They work closely with data scientists to understand data requirements, clean and organize data, and build efficient, scalable capabilities. The role requires a strong foundation in software engineer, statistics, and AI/ML concepts. Due to the fast-paced change in AI/ML, ML Engineers are expected to keep aware with the latest advancements in artificial intelligence and machine learning technologies, ensuring that solutions are both innovative and effective. Collaboration with cross-functional teams is essential to integrate ML models into larger systems and applications. Knowledge of DevOps and MLOps is needed to ensure they can integrate with wider delivery teams.What you could be doing for us: Engineer and implement machine learning (ML) solutions: Able to own the end-to-end process and lifecycle of ML systems.Deploy models and capabilities: Handle the technical aspects of bringing models into a production environment.Research new techniques: Continuously explore the latest ML and AI advancements to identify methods that can enhance current systems.Collaborate with data scientists: Work closely with data scientists to refine, optimise, and implement models based on prototypes.Integrate models with delivery teams: Work as part of a wider delivery team to incorporate models into systems we design and deliver.Data management: Ensure the quality and accessibility of data used for machine learning projects is appropriate, collaborating with data engineers as necessary.Data analysis: Perform analysis of large datasets to uncover trends, patterns, and insights that inform model development and deployment.Monitor model performance: Regularly evaluate deployed models, identifying performance gaps and opportunities for optimisation.Define and optimize MLOps processes: Create and refine the model development and deployment strategy for better efficiency and resultsAdhere to policy and ethical AI standards: Ensure all machine learning practices comply with policy processes and guidelines.Cross-functional technical guidance: Guide cross-functional teams in the implementation and integration of machine learning projects.Innovate and prototype: Develop and deploy ML prototypes within the business, testing feasibility and impact.Cloud Skills and Expertise : Use cloud-based environments to facilitate scalable machine learning model development and deployment across the MLOps lifecycle.Cloud ML Services : Able to integrate pre-built cloud capabilities into a system.What background are we looking for? Data Engineering, Analysis or Science, with a solid understanding of programming languages along with experience of applying them in your previous roleExperience in using Data Engineering tools and technology ETL tools including Python and a number of the Big Data Applications. Rather than specifying a list of technologies we look for, demonstrable ability in what you have used previously, along with adaptability and willingness to learn is what we valueA good understanding of Open Source software for Data Engineering and can evaluate these platforms against products. Given a customer problem you can analyse and evaluate options and recommend solutions.An understanding of maintaining and applies up to date, specialist knowledge of database concepts (including unstructured, NoSQL and "big data" platforms), object and data modelling techniques.Previous experience working in the domain of Cyber Security and Intelligence is desirable, but not essential.How we will support you: Work-life balance is important; you'll get 25 days holiday a year and, via our flexible benefits package the option to buy/sell and carry over from the year beforeYou can work around core hours with flexible and part-time workingOur flexible benefits package includes; private medical and dental insurance, a competitive pension scheme, cycle to work scheme, taste cards and moreYou'll have a dedicated Career Manager to help you develop your career and guide you on your journey through BAEDon't know a particular technology? Your learning and development is key to your future careerYou'll be part of our bonus schemeYou are welcome to join any/all of our Diversity and Support groups. These groups cover everything from gender diversity to mental health and wellbeing.TravelPlease note as a Data Engineer you may be required to work on client sites that are away from your base location. This can be for an extended period of time. In this instance, all travel and expenses costs will be covered. This will not be applicable to all Engineering projects so If you have concerns about this; please speak to your recruitment contact.Security ClearanceOnly those with the permanent and unrestricted right to live and work in the UK will be considered for a position within BAE Systems Applied Intelligence. Due to the nature of our, work successful candidates for this role will be required to go through Government SC clearance prior to starting with us.https://www.gov.uk/guidance/security-vetting-and-clearanceLifeat BAE Systems Digital IntelligenceWe are embracing Hybrid Working. This means you and your colleagues may be working in different locations, such as from home, another BAE Systems office or client site, some or all of the time, and work might be going on at different times of the day.By embracing technology, we can interact, collaborate and create together, even when we're working remotely from one another. Hybrid Working allows for increased flexibility in when and where we work, helping us to balance our work and personal life more effectively, and enhance well-being.Diversity and inclusion are integral to the success of BAE Systems Digital Intelligence. We are proud to have an organisational culture where employees with varying perspectives, skills, life experiences and backgrounds - the best and brightest minds - can work together to achieve excellence and realise individual and organisational potential.

National AI Awards 2025

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.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.