Snabbfakta

    • Cambridge

Ansök senast: 2024-08-23

Research Engineer

Publicerad 2024-06-24

The Opportunity

As a Research Engineer , you will apply software engineering skills to turn analytical innovations from ideas into prototypes and products addressing real-world problems, and you will build and adapt the software and hardware infrastructure that supports our research work. This role is ideally suited for a software engineer with a strong ability to navigate uncertainty, a passion for AI, and some experience working in a team in industry. Expertise in an area of AI would be a bonus.

You will join our Innovation Lab, a team of research scientists and engineers who value collaboration and knowledge exchange.The Lab develops new technologies involving deep neural networks, LLMs, self-supervision and privacy-enhancing technologies.Our current tech stack includes Python, TensorFlow, PyTorch, ClickHouse, Slurm, AWS, Terraform and Docker. However, we strive to pick the right tools based on the job, so there is scope for exploring new tools.

Note that our Research Engineer role is predominantly a software engineering role. If you are more interested in applied ML research, consider applying to our Research Scientist role instead. To help us review your application, please ensure that your motivation for applying to the Research Engineer role is clear from your CV or cover letter.

This is a hybrid role based in our  Cambridge  office, so you will ideally be comfortable coming into the office once or twice a week. If you’re interested in the role but require more flexibility, please speak to us!

Day to Day

Innovation

  • Scope, design and implement prototypes to demonstrate analytical innovations
  • Assist in research programs by performing experimentation under supervision
  • Track cutting-edge literature in order to quickly adopt and implement new technologies
  • Software

  • Build, maintain and adapt software and hardware infrastructure required for research work
  • Champion software engineering best practices and processes across the Innovation Lab
  • Identify and manage technical debt to improve product quality
  • Review code of other team members
  • Communication

  • Interface with stakeholders within the business to understand analytical requirements and opportunities
  • Disseminate research results to Analytics stakeholders within the business
  • Share knowledge of analytical techniques and tooling across delivery and engineering teams
  • Contribute to brainstorming discussions and idea generation
  • About you

    Must haves:

  • Academic background in a relevant discipline, e.g. Computer Science, Mathematics, Physics, or Engineering
  • Experience of designing, developing, maintaining and evolving scalable applications in Java, Python or a similar language, ideally within a software engineering team
  • Experience with deep learning frameworks such as TensorFlow, PyTorch
  • Experience with deploying and scaling cloud-native applications (AWS, Kubernetes, etc.)
  • Knowledge of, or previous experience with, training and evaluating machine learning algorithms
  • Familiarity with modern IDEs, source control, testing and code review practices
  • Experience with working in a Linux environment
  • Ability to manage and prioritise personal workload
  • Great to haves:

  • Knowledge of Machine Learning or Artificial Intelligence to Master’s level
  • Experience with performance tuning and profiling
  • Knowledge of database architectures and data layouts for efficient processing
  • Understanding data pre-processing requirements for machine learning algorithms
  • Knowledge of or previous experience with deploying machine learning algorithms
  • Experience working with large data sets
  • Equal Opportunities

    Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.

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