Machine Learning/Software Engineer Intern
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ABOUT MULTUS
Our mission is to transform human and planetary health by designing cell culture media to fuel the industrial bioeconomy.
We serve companies in the cellular agriculture, advanced therapies and the biopharmaceutical sectors, developing and supplying cell culture media to accelerate their transition from lab to market.
If you are passionate about driving the growth of a sustainable bioeconomy we encourage you to apply and play your part in creating a better future for people and the planet!
ABOUT THE ROLE
This internship offers the opportunity to contribute to a high-impact R&D project at the intersection of machine learning, software engineering, and biotechnology. The work supports the development of computational tools that enhance how we collect, process, and learn from experimental data — helping to improve data quality, consistency, and the speed of our optimisation workflows.
Interns will explore and develop methods that combine software engineering with machine learning to build robust, reusable analytical pipelines. The project involves working with rich experimental datasets and developing approaches to extract reliable, quantitative insights from complex biological data.
This is a genuine blend of software engineering (building well-architected, maintainable systems) and data science/ML (training and evaluating models), making it ideal for candidates who enjoy working across both disciplines.
The role is ideal for students with a strong interest in applied machine learning, software engineering, or data science — particularly in scientific or industrial research contexts.
The internship is a paid fixed-term full-time contract for a minimum of three months, with a flexible start date in summer 2026. We welcome applications from students and recent graduates from any university.
RESPONSIBILITIES
- Exploring and evaluating a range of machine learning and analytical approaches to extract quantitative insights from complex biological data
- Building reproducible computational pipelines for training, evaluating, and deploying ML models
- Working with deep learning architectures and exploring the use of transfer learning to adapt models across different experimental contexts
- Developing tooling and infrastructure to support standardised, repeatable analytical workflows
- Working with large-scale experimental datasets
- Collaborating with cross-functional teams to integrate computational outputs into experimental workflows
SKILLS & EXPERIENCE
- Proficiency in Python, with experience writing clean, well-structured, and maintainable code
- Familiarity with machine learning and deep learning frameworks such as PyTorch, TensorFlow, or Keras
- Proficiency in data manipulation and analysis, including data cleaning, feature engineering, and model evaluation
- Experience with version control systems like Git, supporting collaboration and efficient code management
- Strong foundation in mathematics and statistics, particularly linear algebra, calculus, and probability theory
- Excellent problem-solving and critical thinking abilities, with a capacity to work both independently and as part of a team
- Strong communication skills for presenting complex technical concepts to non-technical stakeholders
- Ability to demonstrate initiative, proactive problem-solving, and comfort with ambiguity
- Enthusiasm for contributing to a fast-paced and interdisciplinary environment, with an eye for detail and code quality
- Passion for learning new technologies and a strong curiosity to explore unknown areas
- Right to work in the UK
The following skills and experiences would help you stand out even more:
- Experience with computer vision or image processing (e.g. OpenCV, scikit-image, or similar)
- Familiarity with transfer learning and fine-tuning pre-trained models on domain-specific data
- Experience building data pipelines or working with large-scale datasets
- Understanding of software engineering best practices: testing, CI/CD, containerisation (e.g. Docker)
- Exposure to MLOps tooling for experiment tracking and model management (e.g. MLflow, Weights & Biases)
OUR HIRING PROCESS
- Application Closes: Rolling - we will review the applications on a rolling basis
- Round 0. Apply online
- Round 1. Task
- Round 2. 60-minute panel interview to discuss the task and interests
BENEFITS
- Salary
- 25 days' holiday + flexible bank holidays (pro-rata)
- Flexible working hours
- Collaborative and driven team
- Company socials and office snacks
OUR VALUES
TENACITY – WE TRY THINGS WITHOUT THE FEAR OF FAILURE
COLLABORATION – WE WORK TOGETHER INCLUSIVELY, CONSTRUCTIVELY & EFFICIENTLY
CANDOUR – WE TALK TO EACH OTHER WITH RESPECT AND INTEGRITY
OUR ED&I STATEMENT
- Multus is an equal-opportunity employer committed to providing a working environment that embraces inclusion, diversity, and belonging. At Multus, we are committed to creating an environment where everyone feels they belong, are enabled to thrive, are respected for who they are, know that they matter, and are empowered to contribute meaningfully. We believe that diverse perspectives and inclusive collaboration drive innovation and make us stronger together.