Degree in Computer Engineering
Docker, Machine learning techniques, Python Programming, PyTorch, Scikit-learn, TensorFlow
What You'll Be Doing
You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the Retail and Consumer space - examples of which can be found here.
You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical and non-technical stakeholders to deploy ML to solve real-world problems. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.
The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:
We’re a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:
Who We're Looking For
At Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation.
We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:
To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):
We build and deploy safe AI systems that combine the best of human and artificial intelligence to help our customers achieve exceptional performance.