Senior Design Authority

Copello
Harlow
10 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer (GCP)

Lead Data Engineer (GCP)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Data Engineer

Senior Data Engineer

Senior Systems and Hardware Design Authority

Location-Harlow

Contract-Permanent


Summaryof Role:

This is an exciting opportunity for a Senior Systems and Hardware Engineer to work within the Assured Position Navigation and Timing Systems team (APNT), producing Digital GPS Anti-Jam Systems and Alternative Navigation Solutions primarily for the military market.

The role will provide Design Authority (DA) support across a range of APNT products, providing Systems and Hardware Engineering expertise/direction across the product lifecycle, from requirements capture, Analysis, Design through to testing, qualification, certification and in-service support.

Main Duties:

This role will initially provide support to the Lead Design Authority for our Flagship Anti-Jam products with a view to becoming the Lead Design Authority once enough training and experience has been gained.

Main activities include DA support to: Customer Programme Management Reviews (including attendance to PMR held in Georgia every 6 months, April and October), monthly customer IPT meetings, weekly internal IPT obsolesce, risk and FRACAS reviews.

Primary responsibilities include production support and obsolescence maintenance, management of project requirements, generation of technical documentation, systems analysis, hardware design, participation in technical design reviews and technical direction/custodianship of the products.

Candidate Requirements:

Essential

  • Experience across the systems engineering lifecycle from requirements through to project completion.
  • Experience with generation of technical documentation at all levels from requirements capture through to Declaration of Design & Performance (DDP).
  • An understanding of the rules of change management and configuration management in a highly regulated industry where safety and performance are paramount
  • Understanding of policies, practises and procedures, and the ability to communicate these to their team.
  • Sense of ownership, resilience and decisiveness to provide technical direction/guidance in the development of electronic solutions, and have the confidence and experience to assess and sign off on solutions

Desirable

  • Experience with the IBM Rational DOORS toolset (or similar)
  • Experience with RF (including Antennas) and Digital Hardware design and test
  • Algorithm development incorporating Modelling experience in MATLAB/Simulink
  • Experience with SysMl or UML in a Systems Engineering environment
  • Experience with configuration management system


JBRP1_UKTJ

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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.