About the role

This an exciting opportunity to join a team at the forefront of artificial intelligence and machine learning.

You will be working in highly collaborative, interdisciplinary teams delivering customer value through the development and refinement of cutting edge ML tools for verification and validation. Through the application of these tools you will help ensure the quality of the probabilistic modelling and reinforcement learning algorithms and provide support and solutions to product and research teams.

You will be developing software for our AI platform and agents to deliver completely new solutions to simulation, finance, logistics and beyond. This means that the work will be varied as you rotate between client projects and internal product development. Your work will be directly used and built upon in our products.

What will you be responsible for?

  • Designing and implementing state-of-the-art engineering and machine learning techniques to solve a variety of different verification problems arising in our customer pilots or products.
  • Developing high quality software alongside our research, data science and product teams.
  • Reviewing documents, designs, and colleagues’ code and providing constructive feedback.
  • Working with researchers and platform engineers to migrate research prototypes to production by ensuring the quality and robustness of the solutions developed.
  • Continuously developing your own machine learning and engineering skills and helping others to improve theirs.
  • Contributing to a culture focussed on quality through mentoring, lightning talks, lunch and learns and reading groups.
  • In your role as a Machine Learning Verification Engineer, the ultimate measure of your success is adoption of the tools and methods you develop within the company.

You will have the opportunity to work on problems in many different product verticals, such as finance and logistics. 

Some of the technologies you'll be working with:

  • Python
  • NumPy
  • TensorFlow
  • Git
  • Cloud computing platforms

What skills, experience, and qualifications do you need to succeed in this role?

  • Prior practical industry experience using software engineering or machine learning to build complex systems
  • Good grasp of both machine learning and software engineering fundamentals
  • Deep knowledge of a programming language (e.g. Python, C++, Java or C#) or working knowledge of multiple languages
  • Degree or higher in computer science, mathematics, machine learning or a similar area, or equivalent experience

One of the great things about working at PROWLER.io is that we prioritise your learning and development as well as knowledge transfer, that’s why we’re looking for someone who is proactive about improving their engineering and ML knowledge and works on their learning by identifying relevant courses, conferences or pursuing self-study as needed. In return, we will make sure you have the time and resources to do this. We encourage knowledge sharing through regular seminars, lightning talks and training days we also host and attend local meet ups.

About PROWLER.io

We are world-class, cross-disciplinary team of researchers, engineers and product managers in Cambridge, UK, the global centre of AI excellence, combining branches of mathematics and engineering in ways that have never been done before. This integrated approach - and our industry-leading research credentials - gives us a unique competitive advantage.

We take pride in our diversity, valuing the experience and expertise that people from different backgrounds bring to our organisation. Our team of over 100 talented people from all over the globe consists of almost 30 different nationalities and we are growing. We are collaborative, innovative, ambitious, optimistic and curious.

We believe AI is valuable only when it enables better decisions. We want to ensure that business is powered by people; empowered by AI.

Salary

Competitive salary, depending on experience. Stock options and comprehensive benefits.

Vacancy application start date: 1 October 2019

Closing date: 29 October 2019


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