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- Tasks: Set up Redis clusters and implement real-time data pipelines using Kafka and Flink.
- Company: Join a forward-thinking tech company in the heart of London.
- Benefits: Hybrid work model, competitive pay, and opportunities for skill enhancement.
- Why this job: Dive into machine learning and make a tangible impact on innovative projects.
- Qualifications: 4-5 years of AWS and machine learning experience required.
- Other info: Exciting 5-month project with potential for extension.
The predicted salary is between 48000 - 72000 £ per year.
Duration: 5 Months + with possible extension
Hybrid: Weekly twice
Location: London UK
Overview
Responsibilities
- Redis cluster setup
- Kafka/Flink streaming pipelines
- S3 Data pipeline
- Real time micro batches implementation (5 minutes, hourly, daily)
- Mongo/Atlas as alternative implementation (we might land with S3 instead)
- SageMaker MLOps / SageMaker Training / SM Model Deployment
- Pytorch
Qualifications
Required Skills:
- Minimum 4-5 years AWS and Machine learning experience in a commercial project.
- Minimum 2-3 Project counts in AWS projects and ML Projects.
Machine Learning Engineer in London employer: Kryptos Technologies UK Limited
Contact Detail:
Kryptos Technologies UK Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning Engineers. 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 and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of Redis, Kafka, and SageMaker. Practise coding challenges and be ready to discuss your past projects in detail – they want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS and machine learning projects. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects!
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 your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any cool projects involving Redis, Kafka, or SageMaker, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions where possible.
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 from our team!
How to prepare for a job interview at Kryptos Technologies UK Limited
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like AWS, SageMaker, and Pytorch. Brush up on your experience with Redis, Kafka, and MongoDB too, as these are crucial for the role.
✨Prepare Real-World Examples
Think of specific projects where you've implemented machine learning solutions or set up data pipelines. Be ready to discuss challenges you faced and how you overcame them, especially in a commercial setting.
✨Understand the Company’s Needs
Research the company’s current projects and how they utilise machine learning. Tailor your answers to show how your skills can directly benefit their goals, particularly in real-time data processing and MLOps.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s workflow, the tools they use, and their approach to machine learning projects. This shows your genuine interest and helps you gauge if the company is the right fit for you.
