Machine Learning Engineer
// Who are we?
Hazy is an AI start-up that helps people to use data whilst treating it responsibly. We’re a spin-out from the University College London’s (UCL) Centre for Computation, Mathematics and Physics. In 2018 we secured $1 million in funding after winning the Innovate AI award from Microsoft’s venture fund (M12) - they identified us as one of the most innovative companies harnessing the power of artificial intelligence. Alongside this, we have secured the backing from some of Europe’s most influential Investors.
Our team is comprised of a diverse group from around the globe and we are all committed to striving for transparency and excellence in everything we do. If you're interested in joining a business at the cutting edge of AI and you're eager to make a difference in the realm of privacy and data ethics, we’d love to hear from you.
// What are we doing?
Hazy uses AI techniques to generate synthetic data to remove the data privacy concerns companies have when using sensitive data. This makes it simpler to innovate with data because it is easier to use and share. Our customers use Hazy to empower their data teams to get more out of their data in a safer way and help protect the people within that data.
We’re at an exciting point in our development. The founding team have defined strong product market fit and are now looking to capitalise on a defined opportunity to build up to Series A funding.
// The Role
Hazy is looking for a talented Machine Learning Engineer to collaborate closely with our team of world-class data scientists to productionise Machine Learning models.
You’ll have the opportunity to lead by example and contribute to the foundations of a progressive, diverse, cross-disciplinary and high-performing Engineering culture.
- Taking ownership of the Hazy code-base to ensure the smooth and efficient integration of new algorithms
- Working closely with our Data Scientists to design and develop machine learning and deep learning systems
- Running machine learning tests and experiments
- Implementing appropriate ML algorithms
- You will be empowered and supported in driving positive change across culture, process, technology and execution.
- Strong Python knowledge
- Familiarity with Python testing frameworks and Continuous Integration systems
- Familiarity with common ML/ Data Science tools:
- Pandas/ Numpy
- Scikit learn
- Tensorflow / Keras
- Graphing / Visualization tools
- Proven history of productionising Machine Learning models, including:
- Docker and build/packaging systems
- Exception handling / error reporting in production (Sentry etc)
- Monitoring and logging systems
- Working with schemas and schema migrations
- Solid understanding of mathematical techniques underlying prediction / classification systems / Neural networks
- Good foundation in basic statistics
- Working knowledge of Unix and common Unix tooling
- Experience with github workflow
- Previous experience of reviewing academic papers and implementing algorithms
- Track record of collaborating effectively within a cross-disciplinary Data Science / Engineering team
Beneficial but not essential:
- Experience with big data systems (spark/ hadoop/ etc)
- Knowledge of C++ / Scala
// What else is on offer?
- Lovely bright office in one of London’s best co-working spaces (a stone’s throw from Old Spitalfields Market - you will never go hungry again..)
- State of the art kit - let us know what tools you need to do your job to the best of your ability
- Generous holiday allowance
- We take your personal, and career development really seriously - we’ll work closely together to scope out clear objectives and goals that will ensure you keep developing.
Hazy is committed to creating and sustaining a working environment in which everyone has an equal opportunity to fulfill their potential. We welcome applications from suitably qualified people from all sections of the community, regardless of their race, sex, disability, religion or belief, sexual orientation or age.