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- Tasks: Architect a cutting-edge Context Engine to tackle cybersecurity challenges.
- Company: High-growth AI startup revolutionising cybersecurity with innovative solutions.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Why this job: Lead impactful projects that redefine data modelling and AI in cybersecurity.
- Qualifications: Experience in ML engineering and building complex data pipelines.
- Other info: Join a dynamic team backed by top-tier VCs and shape the future of cybersecurity.
The predicted salary is between 72000 - 108000 £ per year.
You will architect a sophisticated Context Engine that resolves the volume crisis in cybersecurity, bridging rigid infrastructure data with semantic LLM reasoning. You will transform thousands of raw alerts into actionable focus areas using entity resolution, multi‑membership clustering, and deterministic logic guardrails.
Location: London, UK
Why this role is remarkable:
- Lead the development of a core engine that moves beyond simple LLM wrappers into complex data modeling and explainable AI.
- Join a well‑funded startup backed by top‑tier VCs at an early stage where you define the technical authority and roadmap.
- Solve high‑stakes engineering challenges involving sparse data points, canonical identity resolution, and massive‑scale vulnerability correlation.
What you will do:
- Design a feature engineering layer that translates hard infrastructure signals like IPs and CNAMEs into inductive biases for LLM reasoning.
- Implement a taxonomy‑driven knowledge injection pipeline using deterministic lookup systems to ensure high‑accuracy domain expertise.
- Create a logic layer for entity resolution to resolve canonical identities across sparse data points and define asset boundaries.
The ideal candidate:
- Proven experience building complex data pipelines where LLMs are integrated as components rather than standalone solutions.
- Strong background in ML engineering, specifically categorical data normalization, feature engineering, and agentic workflow orchestration.
- Solid understanding of security literacy, including vulnerability patterns, infrastructure networking concepts, and deterministic deduplication methods.
Next steps:
Visit our website. Click 'Talk to Jack'. Talk to Jack so he can understand your experience and ambitions. Jack will make sure Jill (the AI agent working for the company) considers you for this role. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction. If not, Jack will find you excellent alternatives. All for free.
Lead ML Architect at high-growth cybersecurity AI startup employer: Jack & Jill/External Ats
Contact Detail:
Jack & Jill/External Ats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Architect at high-growth cybersecurity AI startup
✨Tip Number 1
Get to know Jack! He’s your go-to AI for understanding your skills and career goals. A quick chat with him can help tailor your approach and make you stand out.
✨Tip Number 2
Don’t just wait for job postings; actively engage with our website. Regularly check for updates and opportunities that might not be widely advertised.
✨Tip Number 3
Prepare for your chat with Jack by thinking about your past experiences and how they relate to the role. Highlight your expertise in ML engineering and cybersecurity to make a strong impression.
✨Tip Number 4
Be open to feedback! If Jill suggests alternatives, consider them seriously. Sometimes the best opportunities come from unexpected places.
We think you need these skills to ace Lead ML Architect at high-growth cybersecurity AI startup
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Lead ML Architect role. Highlight your experience in building complex data pipelines and integrating LLMs, as this is key for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about cybersecurity and AI. Share specific examples of your past work that demonstrate your expertise in feature engineering and entity resolution.
Showcase Your Problem-Solving Skills: In your application, don’t just list your skills—show us how you've tackled high-stakes engineering challenges before. We want to see your thought process and how you approach complex problems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to get your application into the right hands and ensure Jack can connect with you about your experience and ambitions.
How to prepare for a job interview at Jack & Jill/External Ats
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around ML engineering and data pipelines. Brush up on your knowledge of entity resolution, feature engineering, and how LLMs can be integrated into complex systems.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly those involving sparse data points or vulnerability correlation. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your analytical thinking.
✨Understand Cybersecurity Fundamentals
Since this role is in a cybersecurity startup, it’s crucial to have a solid grasp of security literacy. Familiarise yourself with common vulnerability patterns and infrastructure networking concepts to demonstrate your expertise and relevance to the role.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s vision for the Context Engine and how they plan to tackle high-stakes engineering challenges. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
