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- Tasks: Join a dynamic team to develop cutting-edge machine learning solutions for smart transport.
- Company: A leader in smart mobility and intelligent transport solutions with decades of innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact on safer, greener travel using advanced technologies.
- Qualifications: 5+ years in ML/Data Science, experience with NVIDIA DeepStream, and strong Python or C++ skills.
- Other info: Collaborative environment with exciting projects and career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Your new company is a long-established leader in smart mobility and intelligent transport solutions, with decades of innovation in traffic data, road safety, and network optimisation. It designs and delivers advanced technologies—from intelligent road-safety products to real-time traffic monitoring and analytics—helping transport operators improve journey safety, reduce congestion, and support more sustainable travel. Its solutions empower customers with actionable insights that enhance how people move across transport networks, contributing to safer, greener and more efficient journeys.
Your new role is a fantastic opportunity to work in a dynamic, cross-functional team with an innovative and forward-thinking approach to problem-solving using modern cloud-native systems to create our products. You will have the opportunity to help shape and guide the development of the product that interacts with various real-world devices throughout the highway network. The platform is built on top of a varied stack that allows it to communicate with real-world IoT devices across the UK and beyond, using multiple AWS services to allow for real-time data capture, feeding a backend service built in Laravel, that provides data to a React.js frontend application. Our new computer vision products are built on the foundations of NVIDIA DeepStream and GStreamer using the NVIDIA Jetson hardware and developed in Python and C++.
The technology stack you will work with includes:
- Linux
- NVIDIA DeepStream
- NVIDIA Jetson
- Docker
- Python
- C++
- GStreamer
- PostgresSQL
- Timescale DB
- AWS Cloud
- AWS SageMaker
- NoSQL (DynamoDB)
What you'll need to succeed:
- Strong knowledge and understanding of ML/Data Science concepts, processes, statistical modelling, data and model pipelining and ML algorithms.
- Commercial experience in delivering customer-facing products to the market that utilise computer vision and machine learning.
- Experience with continuous retraining tools in CI/CD processes for object detection, classification and tracking within computer vision pipelines.
- Open to learning new technologies, including web technologies, to help integrate AI and data visualisation capabilities into our existing platform.
Essential:
- 5+ years of experience working within ML/Data science development.
- Experience using NVIDIA DeepStream and Jetson hardware.
- Practical experience developing ML pipelines and applications using Python or C++.
- Strong understanding of Linux/Unix shell scripting.
Highly Desirable:
- Use of Continuous Integration products (Jenkins).
- Use of containerisation technologies Docker Stack / Kubernetes.
- AWS and AWS SageMaker experience.
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
Machine Learning Engineer in Milton Keynes employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Milton Keynes
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and computer vision. This is your chance to demonstrate what you can do beyond just a CV—make it pop!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss your past experiences. We want to see how you think and tackle challenges!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our innovative team.
We think you need these skills to ace Machine Learning Engineer in Milton Keynes
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with ML/Data Science concepts and any relevant projects you've worked on. We want to see how your skills align with our tech stack!
Showcase Your Projects: Include specific examples of projects where you've used NVIDIA DeepStream, Jetson hardware, or developed ML pipelines. This gives us a clear picture of your hands-on experience and how you can contribute to our innovative team.
Keep It Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We’re excited to see what you bring to the table!
How to prepare for a job interview at Hays
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially NVIDIA DeepStream, Jetson hardware, and AWS services. Be ready to discuss how you've used these tools in your previous projects and how they can be applied to the role.
✨Showcase Your ML Knowledge
Prepare to explain your understanding of machine learning concepts, algorithms, and processes. Think of specific examples where you've successfully implemented ML pipelines or worked on computer vision projects, as this will demonstrate your expertise.
✨Demonstrate Problem-Solving Skills
Since the company values innovative problem-solving, come prepared with examples of challenges you've faced in past roles and how you approached them. Highlight your ability to work in cross-functional teams and adapt to new technologies.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your interest in the company's mission and products. Inquire about their current projects involving IoT devices or how they integrate AI into their solutions. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
