You will be required to deploy software into production by building maintainable, readable, modular solutions using modern software engineering best practices. Be ready to talk about your experiences doing code reviews, building interfaces, and deployment systems. You should have strong opinions about best software engineering practices.
Responsibilities:
- Manage and improve our AI development infrastructure.
- Optimize environments for training and testing deep learning models.
- Build tools to automate manual tasks and visualize experiment data to communicate to the team.
- Strategically guide developers and stakeholders as AI SME during new product development.
- Develop APIs that enable our AI models to communicate with partners and customers.
- Implement security measures to protect our models and data pipelines.
- Collaborate with engineering team to deploy models in production.
If you are missing some of the skills but believe you are the right candidate, tell us why.
Skills and Experience:
- At least 5 years hands-on programming experience working on enterprise products.
- Demonstrated proficiency in multiple programming languages with a strong foundation in a statistical platform such as Python, R, Julia or MatLab.
- Experience building AI models in platforms such as Caffe, TensorFlow or PyTorch.
- Installing Nvidia drivers, Cuda, cuDNN.
- Linux, Kubernetes and Helm Charts.
- Experience with AWS, GCP, Azure, etc a plus.
- OpenCV, Nvidia Docker.
- Deepstream SDK, TensorRT.
- Agile/Jira, Github.
This is not a research role. If your only software experience is quickly hacking Python models using libraries like Numpy and Pandas this job isn’t for you.
Be ready to show us models you have created and discuss them in great detail.
