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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 London with a hybrid work model.
- Benefits: Flexible working hours, competitive pay, and opportunities for skill development.
- Why this job: Dive into machine learning and make an impact with cutting-edge technologies.
- Qualifications: Experience with SageMaker, Pytorch, and data pipeline implementations.
- Other info: 5-month contract with potential for extension and growth in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
Location: London (Hybrid, weekly twice)
Duration: 5 months+ with possible extension
Job Description:
- 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)
Requirements:
- SageMaker MLOps / SageMaker Training / SM Model Deployment
- Pytorch
ML engineer employer: Kryptos Technologies limited
Contact Detail:
Kryptos Technologies limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the ML community on LinkedIn or attend local meetups. You never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SageMaker, Pytorch, or any of the tech mentioned in the job description. This will make you stand out!
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of Kafka, Flink, and data pipelines. Practise coding challenges related to real-time data processing to impress your interviewers.
✨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.
We think you need these skills to ace ML engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML tools like SageMaker and Pytorch. 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 excited about the ML Engineer role and how your background makes you a perfect fit for our team at StudySmarter.
Showcase Your Projects: If you've worked on any cool projects involving Kafka, Flink, or data pipelines, make sure to mention them! We love seeing practical examples of your work that relate to the tasks we need help with.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensures you get all the updates about the process!
How to prepare for a job interview at Kryptos Technologies limited
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Redis, Kafka, and SageMaker. Brush up on your knowledge of MLOps and how to deploy models using SageMaker, as this will likely come up during the interview.
✨Prepare Real-World Examples
Think of specific projects where you've implemented streaming pipelines or worked with data pipelines. Be ready to discuss challenges you faced and how you overcame them, especially in real-time micro-batch implementations.
✨Understand the Company’s Needs
Research the company’s current projects and how they might use ML engineering. Tailor your answers to show how your skills can directly benefit their goals, particularly in areas like S3 Data pipeline and Mongo/Atlas implementations.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s workflow, the tools they use, and their approach to machine learning. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
