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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: Competitive pay, flexible working hours, and opportunities for skill enhancement.
- Why this job: Dive into machine learning and AWS projects that shape the future of technology.
- Qualifications: 4-5 years of AWS and machine learning experience with proven project success.
- Other info: Exciting 5-month contract with potential for extension and career growth.
The predicted salary is between 48000 - 72000 £ per year.
Location: London, UK
Duration: 5 Months + with possible extension
Hybrid (Weekly twice)
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)
- SageMaker MLOps / SageMaker Training / SM Model Deployment
- Pytorch
Requirements:
- 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 limited
Contact Detail:
Kryptos Technologies 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 when a casual chat could lead to your next big opportunity.
✨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 the perfect fit 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 you've worked on!
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 – we love to see your personality!
Showcase Your Projects: If you've got specific projects that align with the tasks listed in the job description, make sure to mention them! Whether it's setting up Redis clusters or working with Kafka/Flink, we want to know what you've done and how it relates to what we do.
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 – just follow the prompts and you’ll be all set!
How to prepare for a job interview at Kryptos Technologies limited
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS, machine learning concepts, and the specific tools mentioned in the job description like SageMaker and Pytorch. Brush up on your experience with Redis, Kafka, and MongoDB too, as these will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss at least two or three of your previous projects that align with the requirements. Be ready to explain your role, the challenges you faced, and how you overcame them, especially in relation to AWS and machine learning.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare some thoughtful questions about the company’s current projects, their tech stack, or how they approach machine learning challenges. This shows your genuine interest and helps you gauge if it’s the right fit for you.
✨Practice Problem-Solving
You might be asked to solve a technical problem or case study during the interview. Practise explaining your thought process clearly and logically. This will demonstrate your analytical skills and ability to work through complex issues, which is crucial for a Machine Learning Engineer.
