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- Tasks: Design and deploy scalable ML pipelines on AWS, focusing on real-time data processing.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Attractive salary, health perks, remote work options, and continuous learning opportunities.
- Why this job: Make a real impact in AI/ML while working with cutting-edge technologies.
- Qualifications: 8+ years in machine learning, strong coding skills in Python, R, Java or C++.
- Other info: Dynamic team environment with opportunities for career advancement.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking an experienced Machine Learning Engineer to design, build, and deploy scalable data and ML pipelines on AWS. The role focuses on real-time data processing, streaming architectures, and end-to-end ML lifecycle management using modern cloud-native technologies. The ideal candidate will have strong experience across AWS services, streaming data platforms, and production-grade ML systems, with hands-on expertise in SageMaker and PyTorch.
Job Description
- Redis cluster setup
- Mongo/Atlas as alternative implementation (we might land with S3 instead)
- Pytorch
- Design machine learning systems: You will work on building and implementing machine learning models and deploying these models into production.
- Data analysis: You will be responsible for improving data quality through data cleaning, validation, and transformation so that it can be used effectively by the machine learning models.
- Educate the team: As our machine learning expert, you will also have the opportunity to teach others about machine learning principles and help them understand how these principles can be applied to our products.
- Stay updated: You should stay abreast of latest trends and developments in machine learning, ensuring we continue to innovate.
Qualifications
- Bachelor's Degree in Computer Science, Statistics, Applied Math or related field.
- 8+ years of practical experience with machine learning, algorithm design, data modeling, and software development.
- Hands-on experience in machine learning, predictive modeling and analysis, and cross-functional collaboration.
- Proficient in Python, R, Java or C++ programming languages.
- Experience with Hadoop, Hive, Spark, SQL or other big data technologies.
- Excellent communication skills, as this role will collaborate with both technical and non-technical colleagues.
AI/ML Engineer in London employer: N Consulting Limited
Contact Detail:
N Consulting Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML field and let them know you're on the hunt for opportunities. Attend meetups or webinars related to machine learning to meet potential employers and learn about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving AWS, SageMaker, and PyTorch. This will give you an edge and demonstrate your hands-on expertise to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with data pipelines and real-time processing, as well as how you've tackled challenges in previous roles.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your relevant experience and passion for machine learning.
We think you need these skills to ace AI/ML Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, SageMaker, and PyTorch. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool ML projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to know what you've built and how it relates to real-time data processing and ML lifecycle management.
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!
How to prepare for a job interview at N Consulting Limited
✨Know Your Tech Stack
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 used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in machine learning projects. Highlight how you approached data cleaning, validation, and transformation to improve data quality for your models.
✨Communicate Clearly
Since this role involves educating the team, practice explaining complex machine learning concepts in simple terms. Be ready to demonstrate your ability to collaborate with both technical and non-technical colleagues.
✨Stay Current
Research the latest trends and developments in machine learning. Be prepared to discuss recent innovations and how they could apply to the company’s products, showing that you’re proactive about staying updated in the field.
