At a Glance
- Tasks: Design and build AI/ML systems and automated pipelines for the insurance sector.
- Company: Join RecOps, a leader in AI/ML projects within the insurance industry.
- Benefits: Earn £575 per day, with flexible remote work and one day onsite in Central London.
- Other info: Opportunity to work in a dynamic environment with potential for career advancement.
- Why this job: Lead innovative ML projects and make a significant impact in the insurance sector.
- Qualifications: Strong Python skills and experience in leading ML projects required.
The predicted salary is between 115000 - 115000 € per year.
RecOps is seeking a Lead Machine Learning Engineer to support an AI/ML project in the insurance sector. The role offers £575 per day, inside IR35, and requires 1 day per week onsite in Central London.
The ideal candidate has strong Python engineering skills, along with experience in leading ML projects and managing production-quality systems.
Responsibilities include:
- Designing AI/ML systems from scratch
- Building automated pipelines
Lead ML Engineer - GenAI, MLOps & Production Systems in London employer: RecOps
RecOps is an exceptional employer that fosters a dynamic work culture, encouraging innovation and collaboration among its team members. With a focus on employee growth, we offer ample opportunities for professional development in the rapidly evolving field of AI and machine learning. Located in the heart of Central London, our team enjoys the unique advantage of working in a vibrant city while contributing to impactful projects in the insurance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML Engineer - GenAI, MLOps & Production Systems in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best ML projects, especially those involving Python and production systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with designing AI/ML systems and managing pipelines, as these are key for the role.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Lead ML Engineer - GenAI, MLOps & Production Systems in London
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your strong Python engineering skills in your application. We want to see how you've used Python in past projects, especially in ML contexts, so don’t hold back!
Lead with Experience:Since this role is all about leading ML projects, share specific examples of your leadership experience. We’re keen to know how you’ve managed teams and production-quality systems in the past.
Designing from Scratch:Talk about your experience in designing AI/ML systems from scratch. We love innovative thinkers, so if you’ve built something unique, let us know how you approached it!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at RecOps
✨Know Your Python Inside Out
Since the role requires strong Python engineering skills, make sure you brush up on your Python knowledge. Be ready to discuss your previous projects and how you've used Python to solve complex problems, especially in ML contexts.
✨Showcase Your Leadership Experience
As a Lead ML Engineer, you'll need to demonstrate your ability to lead projects. Prepare examples of how you've successfully managed teams or projects in the past, focusing on your decision-making process and how you handled challenges.
✨Understand MLOps and Production Systems
Familiarise yourself with MLOps practices and production-quality systems. Be prepared to discuss how you've implemented automated pipelines and ensured the reliability of ML models in production environments.
✨Research the Insurance Sector
Since this role is focused on an AI/ML project in the insurance sector, do some homework on current trends and challenges in the industry. This will help you tailor your answers and show that you're genuinely interested in the field.
