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For Companies At a Glance
- Tasks: Build and improve Python-based ML tools and pipelines for researchers.
- Company: Join a leading tech firm in Cambridge focused on engineering excellence.
- Benefits: Competitive salary, 12-month contract, and potential for extension.
- Why this job: Work hands-on with cutting-edge ML technology and solve real engineering challenges.
- Qualifications: Strong Python skills and experience with PyTorch or TensorFlow required.
- Other info: Collaborate closely with ML researchers in a dynamic, hardware-heavy environment.
The predicted salary is between 85000 - 115000 £ per year.
This role is for a hands-on Python engineer who enjoys building systems and tools that ML researchers rely on to run experiments at scale. No people management. No product features. Pure engineering.
What You'll Do
- Build and improve Python-based ML tooling and pipelines
- Support and scale distributed compute workflows
- Fix, optimise, and own internal systems used daily by ML teams
What We're Looking For
- Strong Python software engineer (4+ years)
- Experience with PyTorch or TensorFlow
- Exposure to distributed systems / large-scale compute
- Comfortable building tools for other engineers or researchers
What’s In It For You
- £98k-£110k PAYE (inside IR35)
- 12-month contract + potential extension
- Fully on-site in Cambridge (hardware-heavy environment)
- Work closely with ML researchers and infra teams
If you like owning systems and solving real engineering problems, let's talk.
Python / ML - Software Developer - Principle in Cambridge employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python / ML - Software Developer - Principle in Cambridge
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML and Python communities. Attend meetups or webinars, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those related to ML tooling or distributed systems. This gives potential employers a taste of what you can do and how you think. We love seeing practical examples of your work!
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. Practice coding challenges and system design questions. We recommend using platforms like LeetCode or HackerRank to sharpen your skills before the big day!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for passionate engineers who want to build tools that make a difference in the ML space. Don’t miss out!
We think you need these skills to ace Python / ML - Software Developer - Principle in Cambridge
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your experience with Python in your application. We want to see how you've used it in real projects, especially in building tools or systems that support ML research.
Talk About Your ML Experience: If you've worked with PyTorch or TensorFlow, let us know! Share specific examples of how you've applied these frameworks in your previous roles. This will help us understand your hands-on experience.
Demonstrate Problem-Solving Abilities: We love engineers who can tackle real problems. In your application, mention any challenges you've faced in distributed systems or large-scale compute and how you overcame them.
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 us!
How to prepare for a job interview at Jobster
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your past projects and how you've used Python to solve complex problems, especially in ML contexts. They’ll want to see your depth of knowledge and practical experience.
✨Familiarise Yourself with ML Tools
Since this role involves building ML tooling, it’s crucial to have a solid understanding of frameworks like PyTorch or TensorFlow. Prepare to talk about your experience with these tools and how you've implemented them in previous projects.
✨Understand Distributed Systems
Given the focus on distributed compute workflows, make sure you can explain how distributed systems work. Brush up on concepts like scalability and performance optimisation, and be ready to share examples of how you've tackled these challenges in the past.
✨Show Your Problem-Solving Skills
This role is all about engineering solutions, so be prepared to discuss specific engineering problems you've solved. Think of examples where you’ve optimised internal systems or built tools that improved workflows for other engineers or researchers.
