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Software Engineer (R03)

digiLab

Exeter

On-site

GBP 40,000 - 80,000

Full time

16 days ago

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Job summary

Join a pioneering AI company that transforms complex challenges into innovative solutions. As a Software Engineer, you will work with a dynamic team to develop The Uncertainty Engine, a no-code AI platform. Your role will involve utilizing your expertise in Python and AWS to create scalable systems while fostering a collaborative environment. Enjoy a unique 4-day workweek that promotes work-life balance, alongside exciting team activities and a culture of innovation. If you're passionate about AI and software engineering, this opportunity is perfect for you!

Benefits

4-day working week
BUPA private health care
Discretionary EMI scheme
Competitive Salary

Qualifications

  • Experience in software development and cloud technologies.
  • Deep understanding of Python and machine learning principles.

Responsibilities

  • Collaborate with teams to design and develop software solutions.
  • Implement security best practices and maintain software quality.

Skills

Python
Cloud (AWS)
Machine Learning
MongoDB
Linux
Git/GitHub
Docker
Statistical Analysis (Numpy, Scipy, Pandas)
Software Design Patterns
CI/CD Pipelines

Education

Degree in Computer Science or related field
Masters-level qualification in a STEM field

Tools

Docker
Git/GitHub
AWS

Job description

Please note that only applications with cover letters will be considered.

Summary:

digiLab is a pioneering AI company that helps enterprises transform complex challenges into innovation with uncertainty quantification, explainable AI and MLOps. Working with organisations in highly regulated or safety-critical industries to solve their complex engineering, infrastructure or data challenges, digiLab specialises in solving problems where data is sparse or uncertain. Having grown from a small team of leading mathematicians and data scientists, digiLab teaches your teams how to solve their grand challenges using a secure AI platform, alongside expert consultancy. digiLab's platform - the Uncertainty Engine is a no-code agentic AI platform that combines data, models and workflows to connect a trustworthy AI digital thread through an organisation.

The full-time role (Monday to Thursday), reporting to the Lead Software Engineer, covering a range of software engineering and machine-learning skills.

What we are looking for:

We are seeking an enthusiastic Software Engineer with cloud (AWS) experience to join our team and contribute to the development of our product, The Uncertainty Engine. The ideal candidate will have experience working with Python and a strong interest or familiarity with machine learning. They should thrive in a fast-paced, collaborative, and dynamic environment.

What you will be doing with us:

As a Software Engineer at digiLab, you will be responsible for:

  • Collaborating with a cross-functional team to design, develop, and maintain high-quality software solutions.
  • Utilizing expertise in AWS, Python, MongoDB, and other relevant technologies to contribute to scalable, secure systems.
  • Applying security best practices throughout the software development lifecycle.
  • Fostering a collaborative, learning-oriented environment within the team.
  • Implementing software design patterns, SOLID principles, and best practices.
  • Demonstrating an understanding of CI/CD pipelines.
  • Providing technical support and participating in incident investigations.
  • Ensuring adherence to RESTful API design principles.

What Skills we are looking for:

  • Industry experience in (scientific) software development.
  • Degree-level qualification in computer science or related field.
  • Professional experience with collaborative software development.
  • Deep understanding of Python.
  • Familiarity with Linux, bash, and the command line.
  • Experience with modern statistical machine learning and AI, including Numpy, Scipy, and Pandas.
  • Ability to write logical, consistent, self-explanatory code.
  • Understanding of software design patterns, SOLID and DRY principles.
  • Experience with Git/GitHub and best practices.
  • Knowledge of the software testing pyramid and types of automated testing (smoke, component, unit, performance, load, end-to-end).
  • Experience with Docker and other containerization platforms.
  • Proven ability to collaborate in a fast-paced 'agile' team, preferably using 'scrum'.

In addition, some nice to haves are:

  • A Masters-level qualification in a STEM field.
  • Experience with front-end development: HTML; CSS; React; Javascript/Typescript.
  • Experience with UI/UX design principles.
  • Experience with PyTorch or other deep-learning libraries.
  • An understanding of Bayesian statistics.

Location:

This role is based on-site at digiLab's offices on the Quay, Exeter.

Our Culture and Values:
At digiLab, we prioritize work-life balance with a 4-day workweek (Monday to Thursday), offering a full-time salary and three-day weekends every week! Our team is built on strong connections, with regular socials like game nights, bouldering, and paddleboarding.

We foster a culture of innovation, trust, and collaboration. Our values include:

  • Creativity & Agility: Encouraging innovation and flexibility in goal achievement.
  • Trust & Responsibility: Supporting each other in taking calculated risks for bold innovation.
  • Open & Honest Collaboration: Ensuring transparent communication and alignment.
  • High-Performance Standards: Continuously challenging ourselves to excel in delivery.
  • Value-Driven Work: Regularly assessing our contributions toward company goals.

Benefits:

We value enthusiasm and loyalty, and we're committed to offering a great work-life balance. Along with the exciting challenges this role provides, we offer a range of benefits including:

  • 4-day working week
  • Competitive Salary
  • BUPA private health care (via salary sacrifice)
  • Discretionary EMI scheme (eligible after one year with the company)

Please note that while we strive to respond to every applicant, due to the high volume of applications, we may not be able to

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