- BS or MS degree in computing or a related field
- 2+ years experience developing and deploying machine learning systems into production
- Through previous formal or “on the job” training, in-depth experience of developing and delivering projects in the areas of Machine Learning, Deep Learning, Computer Vision, Neural Network Architectures, Natural Language Processing, Information Visualization and Data Analytics.
- Proven experience in at least one of the Deep Learning Frameworks (Tensorflow, Pytorch, Torch, Mxnet, CNTK, Apache Mahout, etc.) and related tools in each specialized field
- Strong knowledge of data pipeline and workflow management tools
- Experience with at least one cloud provider solution (AWS, GCP, Azure) and use their APIs
- Relevant working experience with Docker and Kubernetes is a big plus.
Experimentation and Leadership is at the core of what you do. The role is to lead the team working in the domain of AI applications in agriculture, healthcare and visual surveillance automation.
- Explore the literature, formulate the strategy and guide the individuals (team members) on solutions development.
- Manage project execution, maintain technical documentation and reporting
- Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation,
- Contribute to and promote good software engineering practices across the team
- Knowledge sharing with the team to adopt best practices, actively contribute to and re-use community best practices
- Assist in writing project applications for funding from national and international competitions
- Assist in Planning, management, and conduct of short trainings and AI skills enhancement bootcamps