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- Tasks: Design and deploy scalable data and ML pipelines on AWS.
- Company: Leading tech company in Greater London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of AI and machine learning.
- Qualifications: 8+ years in machine learning with expertise in AWS and streaming data platforms.
- Other info: Stay ahead in the field while educating and inspiring your team.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology company in Greater London is looking for an experienced Machine Learning Engineer to design and deploy scalable data and ML pipelines on AWS. The ideal candidate will have over 8 years of experience with machine learning and strong expertise in AWS services, streaming data platforms, and production-grade ML systems, particularly with SageMaker and PyTorch. This role also involves educating the team and staying updated on the latest developments in machine learning.
Real-Time AI/ML Engineer — AWS, Streaming & MLOps employer: Natobotics
Contact Detail:
Natobotics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Real-Time AI/ML Engineer — AWS, Streaming & MLOps
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML space and let them know you're on the hunt for a role. 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 AWS, SageMaker, and PyTorch. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Stay updated! Follow the latest trends in machine learning and AWS services. Join online forums or attend meetups to discuss new developments. This not only boosts your knowledge but also shows employers that you're passionate about the field.
✨Tip Number 4
Apply through our website! We make it super easy for you to find roles that match your skills. Plus, applying directly gives you a better chance of being noticed by our hiring team. Don't miss out!
We think you need these skills to ace Real-Time AI/ML Engineer — AWS, Streaming & MLOps
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, streaming data platforms, and ML systems. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in SageMaker and PyTorch!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. We love seeing candidates who are excited about educating others and staying updated on industry trends.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them! We want to see real examples of your work with scalable data and ML pipelines. This helps us understand your hands-on experience and problem-solving skills.
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 don’t miss out on any important updates. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Natobotics
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS services, especially SageMaker and PyTorch. Brush up on your knowledge of streaming data platforms and be ready to discuss how you've designed and deployed ML pipelines in the past.
✨Showcase Your Experience
With over 8 years of experience expected, prepare specific examples from your previous roles. Highlight projects where you’ve successfully implemented production-grade ML systems and how you’ve contributed to team education.
✨Stay Current with Trends
The tech world moves fast! Be prepared to discuss the latest developments in machine learning. This shows your passion for the field and that you’re proactive about staying updated.
✨Ask Insightful Questions
Interviews are a two-way street. Prepare thoughtful questions about the company’s approach to AI/ML, their tech stack, and how they foster team learning. This not only shows your interest but also helps you gauge if it’s the right fit for you.
