At a Glance
- Tasks: Lead the design of scalable ML systems and ensure compliance with enterprise standards.
- Company: LSEG, a diverse and inclusive tech leader in Greater London.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Join a dynamic team committed to innovation and excellence.
- Why this job: Shape the future of ML technology and make a significant impact.
- Qualifications: Expertise in AWS SageMaker, Python, and experience in production ML systems.
The predicted salary is between 80000 - 100000 € per year.
LSEG in Greater London is seeking a Principal Machine Learning Engineer to provide technical leadership for a new matching platform. The role requires expertise in AWS SageMaker, Python, and MLOps for designing scalable ML systems.
Key responsibilities include:
- Defining ML architecture
- Driving model governance
- Ensuring compliance with enterprise standards
Candidates should have experience in building production ML systems and a strong grounding in explainability and telemetry. This position supports a diverse and inclusive workplace.
Senior ML Platform Architect - SageMaker & MLOps in London employer: LSEG
LSEG is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. With a strong commitment to employee growth, we provide ample opportunities for professional development and advancement in the rapidly evolving field of machine learning. Our inclusive environment not only values diversity but also encourages creative problem-solving, making it a rewarding place for those looking to make a meaningful impact in technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Platform Architect - SageMaker & MLOps in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work with AWS SageMaker and MLOps. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ML architecture and production systems. This is your chance to demonstrate your expertise in Python and model governance.
✨Tip Number 3
Prepare for interviews by brushing up on explainability and telemetry concepts. Be ready to discuss how you've tackled these in past projects. We want to see your thought process and problem-solving skills!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior ML Platform Architect - SageMaker & MLOps in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AWS SageMaker, Python, and MLOps. We want to see how your skills align with the role, so don’t be shy about showcasing your past projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about building scalable ML systems and how your expertise can contribute to our new matching platform. Keep it engaging and relevant!
Showcase Your Technical Leadership:Since this role involves technical leadership, share examples of how you've led teams or projects in the past. We love seeing candidates who can drive model governance and ensure compliance with enterprise standards.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at LSEG
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS SageMaker, Python, and MLOps. Brush up on your knowledge of scalable ML systems and be ready to discuss your past experiences with building production ML systems. This will show that you can hit the ground running.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about ML architecture and model governance. Prepare examples from your previous work where you’ve defined architectures or ensured compliance with enterprise standards. This will demonstrate your hands-on experience and problem-solving skills.
✨Showcase Your Understanding of Explainability
Since explainability and telemetry are key aspects of the role, be prepared to discuss how you’ve implemented these in your past projects. Bring specific examples that highlight your approach to making ML models interpretable and how you’ve monitored their performance.
✨Emphasise Diversity and Inclusion
LSEG values a diverse and inclusive workplace, so be ready to share your thoughts on how diversity can enhance team performance. Discuss any experiences you have working in diverse teams and how you’ve contributed to an inclusive environment.
