At a Glance
- Tasks: Build and automate ML pipelines, deploy models, and drive innovation in insurance.
- Company: Intact Insurance, a forward-thinking company transforming the insurance industry.
- Benefits: Annual bonus, hybrid working, 25 days leave, and career development opportunities.
- Why this job: Make a real impact with cutting-edge ML technology while growing your career.
- Qualifications: Experience with ML platforms, Python, and strong collaboration skills.
- Other info: Inclusive culture with flexible working options and support for all applicants.
The predicted salary is between 50000 - 70000 £ per year.
Intact Insurance is the new name for RSA in the UK, Ireland, and across Europe. It’s a new name and a new way to do business. Backed by global expertise and a commitment to service that feels different, we’re focused on making insurance simpler, faster, and more responsive.
Shape the future: We’re leading a transformation in insurance helping people, businesses and society prosper in good times and be resilient in bad times. When you join us, you’re not just taking a job, you’re stepping into a career where you can make a real difference.
Grow with us: We’re customer-driven, community-focused, and committed to helping our people grow. Whether you’re early in your journey or bringing years of experience, we’ll support you with the tools, flexibility, and opportunities to thrive.
Win as a Team: We’re looking for a Machine Learning Engineer to help build and run production-ready ML systems that make a real impact across the business. You’ll work closely with Data Scientists and engineering teams, shaping the ML roadmap, developing scalable solutions, and driving innovation while growing your career.
You’ll make an impact by:
- Building and automating ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
- Productionising Data Science models, converting notebooks into modular, tested, production-ready code.
- Deploying models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
- Implementing monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
- Collaborating with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
- Maintaining engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.
Your skills and experience:
- Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
- Proficient in Python, PySpark, and SQL, following production coding best practices.
- Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
- Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
- Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.
Why You’ll Love It Here: Being part of our team means you’ll have the support and freedom to bring your best self to work each day. As a permanent member, here’s what you can look forward to:
- Annual discretionary bonus
- Up to 11% pension contributions
- Hybrid working + flexible hours
- 25 days annual leave + bank holidays + buy/sell options
- Career development and mentoring
- Inclusive culture + employee networks
- Share investment options
Our DEI Commitment: We celebrate individuality and believe our differences make us stronger. We’re proud to foster a culture where everyone feels respected, valued, and empowered to thrive. As an Equal Opportunity and Disability Confident Employer, we ensure fair consideration for all applicants and offer interviews to all disabled candidates who meet the essential criteria. We understand that everyone’s circumstances are different and are happy to explore flexible working options such as reduced hours or job shares to support work–life balance. If you meet the core criteria but not every requirement, we’d still love to hear from you. Let’s explore how this role could support your next career step. If you need adjustments during the recruitment process, just let us know we’re here to support you.
Machine Learning Engineer employer: RSA Group
Contact Detail:
RSA Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Intact Insurance on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your previous ML projects, especially those involving Python, PySpark, and Databricks. This will give you an edge during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to ML systems and coding. Consider mock interviews with friends or use online platforms to refine your responses and boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows your genuine interest in joining the team at Intact Insurance and being part of their exciting transformation in the insurance industry.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Machine Learning Engineer role. Highlight your experience with Python, PySpark, and any ML platforms like Databricks or MLflow. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for machine learning and how you can contribute to our mission of making insurance simpler and faster. Let us know why you’re excited about this opportunity at Intact Insurance.
Showcase Your Projects: If you've worked on any relevant projects, whether in a professional setting or as personal endeavours, make sure to mention them. We love seeing practical examples of your work, especially those that demonstrate your ability to build and deploy ML systems.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at RSA Group
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, PySpark, and Databricks. Brush up on your knowledge of MLflow and cloud environments, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or deployed ML systems. Highlight your experience with feature engineering, model training, and productionising data science models. Real-world examples will demonstrate your hands-on skills and problem-solving abilities.
✨Understand the Business Impact
Research Intact Insurance and think about how machine learning can transform their business. Be ready to discuss how your work can help make insurance simpler and more responsive, aligning your answers with their mission to support customers and communities.
✨Communicate Effectively
Since collaboration is key, practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with Data Scientists and cross-functional teams, so being able to articulate your thoughts clearly will set you apart.