Job Description And Responsibilities
The Opportunity
Featurespace are looking for a passionate and enthusiastic Software Engineer to join our team. You will work on our industry-leading financial crime fighting technology, making the world a safer place to transact alongside our existing team of innovators and experts.
We are looking for individuals who can deliver and maintain a robust product across the full software development life cycle.
You will help us achieve our goals and deliver success on behalf of our customers by
- Being responsible for analytical technology that is fast, flexible, and easy to use.
- Implementing data intensive applications and machine learning components, enabling Analytics teams to deliver state-of-the-art models in a timely manner.
- Optimising and scaling modelling workflows required to build analytics for increasingly large datasets.
- Implementing new features within ARIC (our software platform) that improves the modelling lifecycle of analytics.
It is first and foremost and engineering role – enabling users to create machine learning and analytics solutions.
This position is based in our Cambridge office, with 3 days per week in the office expected.
Day to Day Responsibilities
Core responsibilities of all members of the team include
- Improving workflows for designing, deploying, and maintaining analytics
- Engineering optimized and maintainable data intensive applications
- Championing software engineering process and process improvements
- Providing support for mission critical services deployed to production including an on-call rota
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications
Basic Qualifications
- Relevant STEM degree (e.g., Computer Science, Engineering, Physics, Maths)
- Experience designing and developing applications in any language
- Understanding of the full SDLC, including source control, testing and code reviews
- Comfortable working with large codebases
- Knowledge of secure software development practices
Preferred Qualifications
- Experience designing and developing applications in Java
- Knowledge of the lifecycle around training and deploying machine learning models
- Knowledge of parallel and distributed computing
- Knowledge of database architectures and data layouts for efficient processing
- Experience with real-time event processing systems
- Experience with performance tuning and profiling
- Ability to design information rich tools in a user-friendly way
- Understanding and use of GenAI technologies in a secure software development lifecycle
- Experience with machine learning frameworks such as Tensorflow or PyTorch
- Experience with working in a Linux environment
