Senior Systems Engineer

Romsey
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Computer Vision Engineer...

Senior Computer Vision Engineer

Senior Machine Learning Engineer

Real-Time Computer Vision Engineer - Production Focus

Senior DSX Data Scientist

Senior DSX Data Scientist

At Roke

Roke is a world-class technology and engineering consultancy. Roke delivers advanced research and development services and products to high profile Customers who come to Roke with varied and challenging problems to solve.

Roke's Defence Business Unit provides technology innovation and consultancy to a variety of military users, applying our skills in Cyber & Networks, Agile Software, Consulting & Systems Engineering, Sensors & Communications, AI & Machine Learning, Information Assurance & Human Science and Data Science.

The Job Opportunity

Roke is seeking Senior Systems Engineers to provide technical leadership in the design and delivery of innovative and effective solutions, across a variety of strategic programmes and business critical initiatives.

The role requires individuals who can work closely with our defence clients and users, applying their technical knowledge and domain experience, whilst communicating effectively with a wide range of internal and external stakeholders.

Individuals must be able to work effectively in a highly technically challenging but rewarding environment, able to quickly assess trade-offs and lead on technical decision making.

Job Purpose & Key Responsibilities

The Senior Systems Engineer is responsible for:
Acting as a System Design Authority across the full engineering lifecycle from initial concept to product.
Providing leadership and systems engineering expertise to technical teams in the delivery of science and technology-based research, solution and product development, equipment trials, and business development including competitive bids.
Strengthening customer relationships and developing business opportunities by providing expert technical assistance in the shaping of solutions and their delivery programmes.
Providing technical assurance expertise across a broad range of internal projects, and on behalf of clients when required.
Liaising regularly with project management teams and Customers for progress reviews, ensuring technical delivery to time, cost and performance/quality whilst managing technical risks.
Working dynamically on Customer sites, from the office, in shared workspaces or from home as required, with occasional overseas travel where necessary. Person Specification
Education and Qualifications
The ideal candidate:
Will have a BEng/BSc and/or master's degree in an appropriate engineering, computer science, information systems or related subject. Knowledge, Skills & Experience
Systems Engineering and technical leadership.
EW familiarity across EA, ES, ECM, ESM, RPNT, RF cyber, middleware and radio bearers.
Defence frameworks and standards such as NAFv4, LCA, MORA, GVA, OpenCPI, AOCO common services and JICD 4.2.
Electronic warfare (C5ISR) and both military and civil communications systems.
Practical electronics experience in hardware, firmware and software including digital signal processing systems/DSPs/FPGAs, software defined radios, RF systems and antennas.
Signal processing principles including sampling, filtering, communications waveforms, protocol stacks, radar and sensor fusion.
Requirements engineering and the analysis of user requirements and use-cases to develop system requirements.
System design elicitation for complex CEMA/RF products and associated R&D programmes.
Familiarity with development processes such as Waterfall, Agile, SAFe and Spiral.
Verification and validation across the full V-model from system level down to lower levels such as circuit verification.
The design and development of technical documentation for engineering projects including user and system requirements, design specifications, test specifications, ITEAPs and VV&T logs.
Identification and analysis of key risks, issues and problems and their associated mitigations and impact and their management through technical RAIDOs. Why You Should Join Us

We have a competitive salary and access to a number of additional flexible benefits, which will cover Health and Wellbeing, Savings and Protection and Life, Leisure and Entertainment.

Roke has a great community of groups with shared interests. These enable people to share ideas and be passionate about tools, technologies and techniques, which interest them.

Security Information

Due to the nature of this position, we require you to be willing and eligible to achieve a minimum of SC clearance. To qualify, the candidate should be a British Citizen and have resided in the UK for the last 5 years for SC

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.

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.