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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: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in AI/ML while working with cutting-edge technologies.
- Qualifications: 8+ years in machine learning, strong programming skills, and a collaborative spirit.
- Other info: Dynamic team environment with a focus on continuous learning and innovation.
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 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
✨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 a new role. Attend meetups, webinars, or conferences to meet potential employers and showcase your skills.
✨Tip Number 2
Show off your projects! Create a portfolio that highlights your machine learning models and data pipelines. Use platforms like GitHub to share your code and demonstrate your hands-on experience with tools like SageMaker and PyTorch.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and data structures, and be ready to discuss your past projects and how you tackled challenges in real-time data processing.
✨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
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, machine learning, and data processing. We want to see how your skills align with the role, 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 AI/ML 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 ML projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they involve tools like SageMaker or PyTorch.
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 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 how they integrate with machine learning systems. Being able to discuss specific projects where you've used these technologies will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss real-world problems you've solved using machine learning. Think about challenges you faced in data cleaning, validation, or model deployment, and be ready to explain your thought process and the impact of your solutions. This will demonstrate your hands-on expertise and analytical skills.
✨Communicate Clearly
Since this role involves collaborating with both technical and non-technical colleagues, practice explaining complex concepts in simple terms. Use examples from your past experiences to illustrate your points. Good communication can set you apart from other candidates.
✨Stay Current with Trends
Research the latest trends and developments in machine learning before your interview. Be prepared to discuss how these trends could apply to the company’s products and how you can contribute to innovation. Showing that you’re proactive about staying updated will reflect positively on your candidacy.
