Senior Security Architect

City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Staff Engineer (ML-Native / Software Engineering)

Senior Data Engineer - DV Cleared

Senior Solutions Architect

Data Scientist - (Senior AI/ML Engineer)

Senior Analyst & Data Specialist

Senior Data Analyst

Senior Security Architect (Architecture & AI Specialist)
6 Months
Hybrid - 1-2 days per week on site in London
£(Apply online only) per day

Please note - The selected candidate MUST HAVE ACTIVE SC Clearance

Overview:
My client in the telecoms industry are looking for a highly skilled and experienced Security Architect with a strong specialisation in Artificial Intelligence (AI) and Machine Learning (ML) security. The role involves significant influence across the organisation, with customers and peers, regarding the strategic contribution of AI/ML security to business objectives.

Essential Skills & Abilities:

Strong strategic cybersecurity experience.
Current Security Professional Certification (CISSP, CISM).
Proven understanding of security frameworks (NIST, ISO 27001, TOGAF, SABSA).
Deep understanding of AI/ML concepts, algorithms, models, regulations and controls.
Extensive technical experience in AI/ML Security Architecture
Proven threat modelling, risk analysis, and architectural validations
In-depth knowledge of adversarial machine learning mitigation.
Comprehensive understanding of ethical AI and governance.
Proven AI security tool implementation and management.
Extensive experience with AI/ML data privacy regulations (GDPR, CCPA).
Strong DevSecOps expertise for AI/ML pipelines.
Good strategic risk analysis and problem-solving.
Good communication and stakeholder influence.
Good cloud security (Azure, AWS, GCP) experience.
Disclaimer:

This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change

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.

Jobs

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!

Jobs Careers

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.