At a Glance
- Tasks: Deploy and maintain cutting-edge AI models and contribute to innovative research projects.
- Company: Join Advai, a leader in AI innovation focused on safety and security.
- Benefits: Enjoy flexible working hours, private health benefits, and professional development opportunities.
- Why this job: Make a real impact in the AI field while working with advanced technologies.
- Qualifications: Degree in Data Science or related field, strong Python skills, and AI engineering experience.
- Other info: Dynamic work environment with excellent career growth in the rapidly evolving AI sector.
The predicted salary is between 36000 - 54000 £ per year.
Job Title: Junior ML Engineer (AI Safety and Security Research)
Salary: £45,000 per annum
Location: London, UK
Type: Full-Time, Permanent
Work Model: Hybrid (Minimum 2 days a week in the office)
About Us:
Advai are at the leading edge of AI innovation, focusing on AI testing and evaluation to help our customers deploy safe and secure AI with confidence. Our mission is to enable AI deployment across government and the economy, to unlock AI’s transformational benefits. As we expand our platform with more automated tooling, we seek a motivated AI Engineer to join our dynamic team in London.
Role Overview:
We are seeking an AI Engineer to deploy and maintain both foundation models (LLMs) and traditional ML systems to support features in Advai’s LLM testing and evaluation platform. Ultimately, you will help build cutting-edge automation into our platform, enabling our customers to achieve scalable confidence in their own AI deployments.
You’ll work across the ML lifecycle, deploying both LLMs and traditional models within production software. You will build and test AI models and APIs, applying your statistical and scientific expertise to design rigorous automation and contribute to and research projects.
The ideal candidate combines technical skills in Python, API design, and cloud-based ML deployment with strong software engineering discipline and a collaborative, proactive mindset.
Must be able to apply for UK Security Clearance: https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levels
Key Responsibilities:
· Deploy both LLMs and classic ML models (e.g. classifiers, detectors) as integrated components within production software.
· Develop and document robust APIs for serving and integrating ML models and AI agents.
· Apply software engineering and deployment practices as needed (e.g., CI/CD, containerisation, orchestration, data pipelines) to support robust and scalable ML delivery.
· Collaborate with research scientists to productionise experimental AI models and integrate them into the company’s tooling and platform.
· Work effectively within Agile teams, contributing to sprint planning, delivery, and continuous improvement.
· Stay up to date with emerging ML frameworks, LLM/agent tools, and deployment strategies, and help evolve internal practices accordingly.
· You’ll work across cloud environments as needed, with a strong emphasis on AWS, which underpins much of our ML infrastructure and workflows.
Requirements:
· Bachelor’s or Master’s degree in Data Science, Machine Learning, Statistics, or a related quantitative discipline.
· Strong proficiency in Python for data science and machine learning application
· Proven experience in AI engineering – designing, building, and scaling ML systems in production environments.
· Experience training or applying machine learning models (LLMs or predictive models), with a strong grounding in scientific and statistical methodology.
· Familiarity with LangChain, PydanticAI, AutoGen, or similar frameworks for building LLM agents and pipelines.
· Software engineering experience, including collaborative development (Git/GitHub), deployment tooling (e.g., Docker, Kubernetes, CI/CD), and good practices in testing, documentation, and maintainability.
· Experience working with AWS or other major cloud platforms.
· Strong analytical and problem-solving skills with a proactive and innovative approach.
· Effective communicator who thrives in a collaborative, hybrid team environment.
Benefits:
· Flexible working hours with a hybrid model, blending in-office collaboration in London with the flexibility of remote work.
· Private health and cycle to work scheme.
· Opportunities for professional development in the rapidly evolving field of AI.
· A dynamic and exciting work environment focused on enabling other organisations to deploy AI with confidence.
How to Apply: Interested candidates are invited to submit their CV, a cover letter, and (optionally) links to project examples to recruitment@advai.co.uk.
We are committed to fostering a diverse and inclusive workplace. We strongly encourage qualified candidates from all backgrounds to apply.
Application Deadline:
Join our journey to help our customers deploy AI that is safe and secure. Propel your career forward with us in London!
Junior ML Engineer (AI Safety and Security Research) employer: Advai
Contact Detail:
Advai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior ML Engineer (AI Safety and Security Research)
✨Tip Number 1
Network like a pro! Reach out to people in the AI and ML community, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and AI. This is your chance to demonstrate your expertise in Python and cloud-based deployments, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common ML interview questions and be ready to discuss your experience with APIs and deployment practices. Confidence is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Tailor your CV and cover letter to highlight your relevant experience and enthusiasm for AI safety and security research.
We think you need these skills to ace Junior ML Engineer (AI Safety and Security Research)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights the skills and experiences that align with the Junior ML Engineer role. We want to see how your background in Python, AI engineering, and cloud deployment fits into our mission at Advai.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI safety and security, and how you can contribute to our team. We love seeing enthusiasm and a proactive mindset!
Showcase Your Projects: If you've worked on relevant projects, don’t hesitate to include links in your application. Whether it's a GitHub repo or a personal website, we want to see your work and how you approach problem-solving in AI.
Apply Through Our Website: While you can send your application to recruitment@advai.co.uk, we encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss any important updates!
How to prepare for a job interview at Advai
✨Know Your Stuff
Make sure you brush up on your Python skills and understand the ML lifecycle. Be ready to discuss your experience with deploying LLMs and traditional models, as well as any relevant frameworks like LangChain or PydanticAI.
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on that demonstrate your AI engineering skills. If you have links to your work, bring them along! This will help you stand out and show your practical experience.
✨Understand the Company’s Mission
Familiarise yourself with Advai's focus on AI safety and security. Be prepared to discuss how your skills can contribute to their mission of enabling safe AI deployment across various sectors.
✨Be Ready for Collaboration Questions
Since you'll be working in Agile teams, think about examples from your past experiences where you collaborated effectively. Highlight your communication skills and how you contribute to team success.