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- Tasks: Lead the development of AI solutions for cybersecurity, enhancing threat detection and incident response.
- Company: Join a top-tier cybersecurity scale-up revolutionising security operations with cutting-edge AI technology.
- Benefits: Enjoy hybrid working, competitive pay, bonuses, and top-notch benefits in a collaborative environment.
- Why this job: Make a real-world impact while working with state-of-the-art AI tools and datasets at scale.
- Qualifications: Experience in machine learning systems, especially in cloud environments, with strong communication skills.
- Other info: Connect with Chris Ryan for a confidential chat about your future in this exciting role.
The predicted salary is between 72000 - 108000 £ per year.
Principal Machine Learning Engineer – Partnering with a Leader in AI-Driven Cybersecurity
Location: Hybrid (Flexible)
Compensation: Market-leading base + Bonus + Benefits
Chris Ryan is proud to be partnering with a top-tier cybersecurity scale-up that's redefining the future of security operations through cutting-edge AI and Machine Learning. This is a unique opportunity to join as a Principal ML Engineer, playing a strategic role in shaping and deploying AI solutions at scale in a mission-critical domain.
About the Role
As a Principal ML Engineer, you'll be at the heart of innovation-architecting and scaling intelligent systems that drive threat detection, incident response, and real-time insights for enterprise users worldwide. This role blends deep technical leadership with real-world impact.
Key Responsibilities
- Develop and deploy scalable ML solutions that directly enhance cybersecurity outcomes.
- Leverage tools such as Amazon SageMaker, Amazon Bedrock, and other AWS services to build secure generative AI applications.
- Design and optimize alert triage systems using NLP, Bayesian modeling, and LLMs to reduce false positives and improve insight generation.
- Collaborate cross-functionally with AI, SecOps, and engineering teams to train, refine, and monitor models in live environments.
- Ensure security, compliance, and reliability of AI solutions in cloud-based infrastructure.
- Shape enterprise AI strategy by guiding customers on secure development, deployment, and monitoring of GenAI tools.
What We're Looking For
- Proven experience designing and deploying machine learning systems in cloud environments (AWS preferred).
- Hands-on expertise with generative AI, LLMs, NLP, and model lifecycle management.
- Strong background in cybersecurity use cases or adjacent domains is a plus.
- Ability to drive strategy and mentor technical teams while staying hands-on where needed.
- Excellent communication skills and a collaborative mindset.
What's On Offer
- A high-impact leadership role in a company solving critical, real-world problems.
- Hybrid working flexibility and a collaborative, fast-paced environment.
- A competitive compensation package, including bonus, pension, and best-in-class benefits.
- The opportunity to work with state-of-the-art AI tooling and real-world datasets at scale.
Interested?
Apply via the link or contact Chris Ryan directly on LinkedIn or WhatsApp for a confidential discussion. With over 20 years of global experience in tech recruitment, Chris is well-placed to advise you on this opportunity and how it aligns with your long-term goals.
Skills:
machine learning AI Cyber
Principal ML Engineer - Driving AI employer: Ocho
Contact Detail:
Ocho Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal ML Engineer - Driving AI
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Amazon SageMaker and AWS services. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Highlight any previous experience you have in cybersecurity or related fields. This role is focused on enhancing cybersecurity outcomes, so demonstrating your understanding of this domain will be crucial in making a strong impression.
✨Tip Number 3
Prepare to discuss your approach to mentoring and leading technical teams. The role requires a blend of leadership and hands-on involvement, so showcasing your ability to guide others while remaining technically engaged will be beneficial.
✨Tip Number 4
Network with professionals in the AI and cybersecurity sectors. Engaging with industry experts can provide insights into current trends and challenges, which you can reference during discussions, showing your proactive interest in the field.
We think you need these skills to ace Principal ML Engineer - Driving AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning systems, particularly in cloud environments like AWS. Emphasise any hands-on expertise with generative AI, LLMs, and NLP, as these are key for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for cybersecurity and how your skills align with the company's mission. Mention specific projects or experiences that demonstrate your ability to develop scalable ML solutions.
Showcase Technical Leadership: Highlight instances where you've driven strategy or mentored teams in your previous roles. This is crucial for a Principal ML Engineer position, so provide concrete examples of your leadership in technical projects.
Prepare for Technical Questions: Anticipate technical questions related to machine learning, AI tools, and cybersecurity. Brush up on relevant concepts and be ready to discuss your approach to designing and optimising ML systems.
How to prepare for a job interview at Ocho
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with machine learning systems, especially in cloud environments like AWS. Highlight specific projects where you've deployed scalable ML solutions and the impact they had on cybersecurity outcomes.
✨Demonstrate Your Knowledge of AI Tools
Familiarise yourself with tools such as Amazon SageMaker and Amazon Bedrock. Be ready to explain how you've used these or similar tools to build secure generative AI applications, and discuss any challenges you faced during implementation.
✨Emphasise Collaboration Skills
This role requires working cross-functionally with various teams. Prepare examples of how you've successfully collaborated with AI, SecOps, and engineering teams in the past, focusing on your communication skills and ability to mentor others.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would approach designing alert triage systems using NLP and Bayesian modelling, and be ready to discuss your thought process.
