At a Glance
- Tasks: Design and build intelligent AI agents for complex workflows using cutting-edge LLM techniques.
- Company: Join a global leader in Insurance and Fintech with a focus on innovation.
- Benefits: Competitive salary, flexible work schedule, and opportunities for professional growth.
- Other info: Stable environment with exciting projects and a strong commitment to ethical AI.
- Why this job: Make a real impact on how millions interact with insurance products through AI.
- Qualifications: Expertise in Python, AI/ML frameworks, and experience with MLOps and cloud platforms.
The predicted salary is between 60000 - 80000 € per year.
Interested in learning more about this job? Scroll down and find out what skills, experience and educational qualifications are needed.
Role: ML Engineer
Type: 12 months Contract
Location: London, UK (2 days per week)
We are looking for a high-caliber AI Engineer to join a global leader in the Insurance and Fintech space. You won't just be building chatbots; you will be designing and orchestrating Autonomous Agentic Systems that reason, plan, and execute complex workflows. This is a unique opportunity to work at the intersection of Generative AI and robust software engineering, applying cutting-edge LLM techniques to high-stakes, real-world data.
What You'll Be Doing:
- Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks.
- LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts.
- Production Engineering: Design and maintain robust ETL/ELT pipelines and manage the lifecycle of models using Docker, Kubernetes, and CI/CD.
- Responsible AI: Ensure our systems are trustworthy by implementing quantifiable metrics for bias detection, explainability, and privacy.
- Performance Tuning: Optimize data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is an added advantage.
Your Technical Toolkit:
- AI/ML: Expert proficiency in Python, PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI.
- Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/NoSQL systems.
- Infrastructure: Proven track record in MLOps, containerization (Docker/K8s), and cloud platforms (Azure/AWS).
- Ethical AI: A deep understanding of AI fairness, transparency, and regulatory compliance within a financial context.
Why This Role?
- Impact: Your work will directly influence how millions of customers interact with insurance products.
- Innovation: Work with the latest LLM architectures (Llama 3.2, Qwen, etc.) in a production environment.
- Stability & Growth: Join a stable, globally recognized institution that is aggressively investing in its AI roadmap for 2026 and beyond.
If you would be interested please share your updated CV on yogeshwari.xwzovohsen@randstaddigital.com with your availability to discuss more about this role.
ML Engineer employer: Randstad Technologies
Join a globally recognised leader in the Insurance and Fintech space, where you will have the opportunity to work on cutting-edge AI technologies that directly impact millions of customers. Our collaborative work culture fosters innovation and growth, providing you with the chance to develop your skills in a supportive environment while contributing to a stable and forward-thinking organisation committed to advancing its AI capabilities. With flexible working arrangements in London, we offer a unique blend of professional development and meaningful work that makes us an excellent employer for aspiring ML Engineers.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow ML enthusiasts. 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 involving LLMs and AI systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates like you. It shows initiative and gives us a chance to see your enthusiasm for the role.
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights the skills and experiences that match the ML Engineer role. Use keywords from the job description to show we’re on the same page about what you bring to the table.
Showcase Your Projects:Include any relevant projects or experiences that demonstrate your expertise in AI/ML, especially with LLMs and production engineering. We love seeing real-world applications of your skills!
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see why you’re a great fit!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at Randstad Technologies
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description. Brush up on Python, PyTorch, and TensorFlow, and be ready to discuss your experience with LLMs and MLOps. Prepare to explain how you've implemented RAG pipelines or worked with containerization tools like Docker and Kubernetes.
✨Showcase Your Problem-Solving Skills
During the interview, be prepared to tackle real-world scenarios that demonstrate your ability to design autonomous systems. Think of examples where you've optimised data workflows or ensured responsible AI practices. This will show your potential employer that you can think critically and apply your knowledge effectively.
✨Understand the Industry Context
Familiarise yourself with the insurance and fintech sectors, especially how AI is transforming these industries. Be ready to discuss trends, challenges, and how your skills can contribute to innovative solutions. This shows that you’re not just a tech whiz but also understand the bigger picture.
✨Prepare Questions That Matter
Interviews are a two-way street, so come armed with insightful questions about the company’s AI roadmap and how they measure success in their projects. This not only demonstrates your interest but also helps you gauge if the role aligns with your career goals.
