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For Companies At a Glance
- Tasks: Build and deploy machine learning models in live pricing systems using Python.
- Company: Join a leading analytics recruitment agency with a focus on innovation.
- Benefits: Up to £40,000 salary, hybrid working, and strong career growth opportunities.
- Why this job: Make a real impact in machine learning operations and learn from experienced engineers.
- Qualifications: Strong Python skills and a passion for machine learning in practical settings.
- Other info: Collaborative environment with modern tools and a focus on long-term technical growth.
The predicted salary is between 24000 - 40000 £ per year.
Salary: Up to £40,000 depending on experience; Location: Manchester - Hybrid working (40% on site increasing to 60% within 12 months).
This is an exciting opportunity to build a career in production machine learning within a large scale pricing and analytics environment. This role is part of a growing Machine Learning Operations team at the heart of a major transformation programme. The focus is on modernising how pricing models are built, tested and deployed into live systems. This role is ideal if you enjoy Python, problem solving and want to understand how machine learning works in real business settings rather than just notebooks. This is not a research focused role and it is not purely infrastructure. The impact happens in the middle, where models become reliable, scalable and ready for customers.
What You Will Be Doing
- Working on Python based rating and machine learning deployments used in live pricing systems
- Supporting testing and analysis to ensure changes are accurate, controlled and high quality
- Building and improving tools, frameworks and APIs that help teams deploy models with confidence
- Collaborating with engineers, analysts and stakeholders to turn ideas into working solutions
- Contributing to clear and well-structured technical documentation
- Developing an understanding of how machine learning impacts customer pricing and business performance
What You Will Bring
- A genuine interest in machine learning systems and how models move into production
- Strong Python fundamentals and a desire to grow your engineering capability
- A degree in a mathematical or technical subject or equivalent practical experience
- Logical thinking and a structured approach to problem solving
- Curiosity, initiative and a willingness to learn
- Clear communication skills and comfort working as part of a collaborative team
You will work on real systems that matter, not isolated exercises. You will be supported by experienced engineers, exposed to modern tooling, and given the space to build confidence in production machine learning and ML Operations. This role is designed to set strong foundations for long term technical growth.
Right to work
You must be eligible and authorised to work in the United Kingdom.
How to apply
Apply to learn more or message for a confidential conversation. If you have a friend or colleague who may be interested, please refer them to us. For each successful placement, you will be eligible for our general gift or voucher scheme.
Junior ML Operations Engineer (Python) in Manchester employer: Guaranteed Tenants Ltd
Contact Detail:
Guaranteed Tenants Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior ML Operations Engineer (Python) in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to machine learning. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML Ops questions and practical scenarios. Practice explaining your thought process clearly, as communication is key when collaborating with teams.
✨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 dive into the world of machine learning.
We think you need these skills to ace Junior ML Operations Engineer (Python) in Manchester
Some tips for your application 🫡
Show Your Python Passion: Make sure to highlight your love for Python in your application. Share any projects or experiences where you've used Python, especially in machine learning contexts. We want to see your enthusiasm shine through!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language and avoid jargon unless it's necessary. We appreciate a well-structured application that’s easy to read!
Demonstrate Problem-Solving Skills: We’re looking for logical thinkers! Include examples of how you've tackled challenges in the past, particularly in tech or data-related scenarios. Show us how you approach problems and find solutions.
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. Plus, it makes the process smoother for everyone involved.
How to prepare for a job interview at Guaranteed Tenants Ltd
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, especially how you've used it in machine learning contexts. Prepare to share specific examples of projects or tasks where you applied your Python knowledge.
✨Understand Machine Learning in Practice
Since this role focuses on production machine learning, it's crucial to understand how models transition from development to deployment. Familiarise yourself with concepts like model testing, deployment strategies, and how machine learning impacts real business scenarios, particularly in pricing.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle some problem-solving questions during the interview. Think about how you approach challenges logically and structure your answers to demonstrate your thought process. Use examples from your past experiences to illustrate your problem-solving capabilities.
✨Communicate Clearly and Collaboratively
This role requires collaboration with various teams, so practice articulating your thoughts clearly. During the interview, show that you're a team player by discussing how you've worked with others in the past. Highlight your communication skills and willingness to learn from colleagues.
