Principal System Engineer - R10187511

Northrop Grumman UK
Harrogate
1 month ago
Applications closed

Related Jobs

View all jobs

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

  • Location:Harrogate, North Yorkshire, United Kingdom
  • Clearance Type:Highest Level of Government Clearance
  • Telecommute:No - Teleworking not available for this position
  • Travel Required:Yes, 10% of the Time
  • Positions Available:1

Define Possible at Northrop Grumman UK

At Northrop Grumman UK, our mission is to solve the most complex challenges by shaping the technology and solutions of tomorrow. We call it Defining Possible.

This mind-set goes beyond our customer solutions; it’s the foundation for your career development and the impact we have within the community. So, what’s your possible?

This is more than just a job; it’s a mission.

As aSystems Engineer, the successful candidate will provide technical planning, cost-benefit analysis, and integration support for operational systems. This Systems Engineer will also serve as an interface between the UK and the US engineering organisations, reporting to the Systems Engineering Manager.You’ll have the chance to work on a programme that is on the front line, supporting operational complex and critical systems as well as innovating and expanding capabilities for the future.

Responsibilities:

  1. Provide engineering support including requirements definition/evaluation, planning, coordination, identifying and addressing impacts, generating documentation, and test support.
  2. Research, prepare and present baseline change proposals to internal and external customers.
  3. Plan, design and support execution of installation and integration activities addressing operational equipment obsolescence and delivery of new systems/capabilities.
  4. Develop and coordinate technical and conceptual trade studies between Site and Factory Operations and Maintenance teams.
  5. Support system engineering functions for the Program including management of project schedules, program risks, opportunities, issues and baseline changes.
  6. Assess program operations and engineering activities to ensure maximum availability, maintainability and overall performance.

We are looking for:

Bachelor of Science Degree in a STEM discipline (Science, Technology, Engineering, Math) or a Master's of Science Degree in a STEM discipline plus relevant technical/engineering experience. For exceptional candidates, we will review experience on a case-by-case basis.

Must be able to thrive and be an effective leader and contributor in a dynamic operational environment working across many organisations and interfaces.

Proven leadership experience on a project and/or team.

Ability to obtain and maintain the highest levels of UK government clearances.

Preferred Qualifications:

Experience with System Engineering foundations and concepts – specific focus on integration, validation and verification.

Experience in the use of LINUX, Perl, MATLAB, AGILE SW development tools.

Security clearance:

You must be able to gain and maintain the highest level of UK Government security clearance. Our requirement team is on hand to answer any questions and we will guide you through the process: .

Ready to apply?

Yes– Submit your application online. Your application will be reviewed by our team and we will be in touch.

Possibly, I’d like to find out moreabout this role – Reach out to our team for more information and support: .

No, I don’t think this role is right for me– Our extensive UK growth means we have exciting, new opportunities opening all the time. Speak to our team to discuss your career goals.

Northrop Grumman is committed to hiring and retaining a diverse workforce, and encourages individuals from all backgrounds and all abilities to apply and consider becoming a part of our diverse and inclusive workforce.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.