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- Tasks: Join a team to deploy machine learning models in live pricing systems using Python.
- Company: Dynamic company transforming pricing and analytics with machine learning.
- Benefits: Up to £40,000 salary, hybrid working, and career growth opportunities.
- Why this job: Make a real impact on business performance through innovative machine learning solutions.
- Qualifications: Strong Python skills and a passion for machine learning in production environments.
- Other info: Collaborative culture with experienced engineers supporting your growth.
Please make an application promptly if you are a good match for this role due to high levels of interest.
Salary: Up to £40,000 depending on experience
Location: Manchester - (Hybrid working - currently 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. You will join 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.
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: Datatech
Contact Detail:
Datatech 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
Prepare for interviews by practising common questions related to Python and machine learning. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format and types of questions you'll face.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant Python or ML projects, make sure to highlight them during interviews. Having tangible examples of your work can really set you apart from other candidates.
✨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 seeing candidates who are proactive about their job search!
We think you need these skills to ace Junior ML Operations Engineer (Python) in Manchester
Some tips for your application 🫡
Show Your Passion for Python: Make sure to highlight your love for Python in your application. We want to see how you've used it in real projects, especially in machine learning contexts. Share specific examples that showcase your skills and enthusiasm!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what makes you a great fit for the role. Remember, less is often more!
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the job description. We’re looking for candidates who understand the role and can demonstrate how their experience aligns with our needs.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Datatech
✨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 in relation to machine learning deployments. Practise coding challenges that focus on Python fundamentals to show off your problem-solving skills.
✨Understand Machine Learning in Production
Familiarise yourself with how machine learning models transition from development to production. Be prepared to discuss real-world applications and the importance of reliability and scalability in live systems. This will demonstrate your genuine interest in the role and its impact on business performance.
✨Prepare for Collaborative Scenarios
Since this role involves working closely with engineers, analysts, and stakeholders, think of examples where you've successfully collaborated in a team setting. Highlight your communication skills and how you’ve contributed to turning ideas into working solutions.
✨Show Your Curiosity and Willingness to Learn
Express your eagerness to grow and learn within the field of machine learning operations. Prepare questions about the team's current projects and future goals to show that you're not just interested in the job, but also in contributing to the team's success.
