Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy scalable ML pipelines using AWS and cutting-edge technologies.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- 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 the latest tech trends.
- Qualifications: 8+ years in machine learning, strong coding skills, and a passion for teaching others.
- Other info: Dynamic team environment with great potential 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.
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
- 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: Natobotics
Contact Detail:
Natobotics 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 opportunities. Attend meetups, webinars, or conferences 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 projects, especially those involving AWS, SageMaker, and PyTorch. This will give you an edge during interviews and help us see your hands-on experience in action.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common algorithms and data structures, and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you’re genuinely interested in joining our team and contributing to our innovative projects in 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, 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 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 practical applications of your skills, especially if they involve real-time data processing or streaming architectures.
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 Natobotics
✨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 like Kafka and Flink, as well as data pipeline setups using S3. Being able to discuss these technologies confidently will show that you're the right fit for the role.
✨Showcase Your Projects
Prepare to talk about specific projects where you've designed and deployed machine learning models. Highlight your experience with real-time data processing and any challenges you overcame. This not only demonstrates your technical skills but also your problem-solving abilities.
✨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
Research the latest trends in machine learning and be ready to discuss them. Showing that you’re proactive about staying updated will impress interviewers and demonstrate your passion for the field. Bring insights or recent developments to the conversation to showcase your enthusiasm.
