RCM/Reliability Engineers

RTP-UK Ltd
Bristol, Bristol (county), United Kingdom
Last month
Posted
15 Apr 2026 (Last month)

As part of the Rheinmetall group, RTP UK are looking to expand its support of internal group products especially in the Defence Air and Space domains, in particular, unmanned system products.

The tasks required will be based around engineering support mainly within Air Systems and particularly unmanned systems, specifically reliability, with the ability to deliver and undertake the following:

• Leading and undertaking Reliability and Safety engineering activities

• Application of the defined System Reliability Centered Maintenance (RCM) and Failure Mode Effects Analysis (FMEA) processes working closely with the Design and Safety functions;

• Analysis of Supportability requirements including, Availability, Reliability and Maintainability (ARM),and RCM across the major system area including modelling and maintainability evaluations;

Core Duties & Responsibilities

• Develop and maintain a thorough knowledge of the System Supportability requirements and drivers.

• Working with clients to develop and perform Reliability Growth Trending and Analysis.

• Working with clients performing Weibull analysis on components and systems on development and in-service programmes.

• Performing Reliability Centered Maintenance Analysis on client programs in accordance with various Standard’s and Client Requirements.

• Development and update of Failure Modes Effects and Criticality Analysis (FMECA) for client projects and programs in accordance with various Standard’s and Client Requirements.

• Investigate and document all data connected with RCM and FMEA activities.

• Undertake AR&M, RCM and FMEA activities.

• Conduct Fault Tree Analysis (FTA).

• Control the AR&M, RCM and FMEA data input process to the LSA data or other repository as required.

• Support or conduct Maintenance Task Analysis (MTA), Level Of Repair Analysis (LORA) and Ease of Maintenance Assessment (EMA) activities.

• Assist in the development of proposals for innovative approaches to RCM and FMEA with the aim of reducing/optimising the Upkeep / Operational cycle for client programs.

• Support, develop and manage client Failure Reporting Analysis and Corrective Action Systems (FRACAS) in accordance with Client requirements and various Standards.

• Ensure data governance, configuration control, validity & integrity.

Behavioral & Role Competences

• A self-motivated and pragmatic individual, with an ability to work effectively as part of a team to deliver successfully to schedule and budget.

• Ability to effectively adhere to flexible work schedules and locations to support the business and work requirements.

• Ability to develop close working relationships with a wide range of stakeholders & interfaces to progress business and program demands.

• Ability to identify value for money options through challenging the norm and implementing innovative solutions.

Essential

• The ideal candidate will ideally have experience in reliability analysis including the application of Mil Handbook 217, Def Stan 00-600, 00-040, 00-042 and the Defence Logistic Framework (DLF).

• Degree, or higher education qualification in engineering, physics or mathematics.

• Experience in the conduct and/or development of Reliability program/regimes in one of the following industries: Aero/Land/Maritime/Energy/Nuclear/Utilities, Transportation or Defence.

Advantageous:

Knowledge/expereince in Unmanned systems

Familiarity with analysis using modern software tools and techniques such as:

o Matlab, particularly involved with Health Monitoring modeling and analysis.

o Monte Carlo Simulations on reliability applications.

o Reliasoft

o Isograph

o RAM

Industry Insights

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

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data Science Jobs UK 2026: roles, salaries and the trends shaping UK data science hiring over the next three years — from MLE crossover to GenAI workflows. Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

New Data Science Employers to Watch in 2026: a UK and international shortlist of analytics and AI companies hiring data scientists, ML engineers and analysts. Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.