Python Developer Anaconda - MedTech

Client Server
Cambridge
1 week ago
Create job alert

Python Developer / Backend Software Engineer (Python Anaconda) Cambridge onsite to £55k


Would you like to work on greenfield projects at the cutting edge of medical technology?


You could be joining a well funded start-up, collaborating with scientists and other engineers to develop sensing and imaging terahertz solutions.


As a Python Developer you'll work on complex problems including image processing, machine learning, numerical simulation, user interfaces, databases, networking and interfacing with hardware. You'll be using an Anaconda based Python stack but with constantly evolving technology that you'll be able to influence.


Location:

You'll join a talented team based just north of Cambridge (with parking available), on a fulltime basis (with some flexibility).


About you:

  • You have strong software engineering experience with Python and ideally also some of the following: Anaconda, Mamba, Poetry, C++, JavaScript, Haskell, OCaml, Rust
  • You have experience working with asynchronous, parallel or distributed systems
  • You have a good knowledge of at least one relational database
  • You have a good understanding of TDD, CI/CD practices and modern software engineering best practices
  • You are degree educated in a relevant STEM discipline
  • You're collaborative, comfortable with Pair Programming and mentoring more junior engineers


What's in it for you:

As a Python Developer you will receive a competitive package:

  • Salary to £55k
  • Bonus
  • Healthcare
  • Pension
  • Continual learning and self development
  • Complex interesting work at the cutting edge of technology


Apply nowto find out more about this Python Developer / Backend Software Engineer (Python Anaconda) opportunity.


At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

Related Jobs

View all jobs

Python Developer

Python Developer - Digital Transformation Team

Python Developer

Python/Data Science Developer

Django Developer

DevOps Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.