A typical day will look like this:
- Participation in the design and scoping of greenfield projects.
- Brainstorm, implement and deliver end-to-end solutions to complex technical. problems— typically starting with spike sessions, followed by the architectural design, iteration on the solution, measuring quality, and ultimately deploying to production.
- Participate in technical discussion and provide feedback.
We are looking for:
- Programming/Tech Environments: Ability to code in scientific python, using a Linux environment, and git for source control.
- Commitment to software engineering principles for scientific python, a keen eye for clean code, and a passion for robustness and correctness.
- Domain Knowledge – Computer Vision: Working on Machine Learning problems related to computer vision applications.
- Deep Learning: Applying modern artificial neural networks to solve real-world machine learning problems using GPUs.
Nice-to-haves:
- Experience with optimisation.
- Experience with deep learning for 3D modelling.
Personal attributes:
- While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.
- Data science is a team sport; communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
- Showing attention to detail when it counts is important; to be considered for this role, click this link and apply some basic data science skills.
