Machine Learning Engineer

M.S. or Ph.D. in computer science, electrical and computer engineering, or related fields.
Minimum 3 years of industry experience developing productionized code in machine learning, data engineering, or related field for AI applications
Excellent communication skills both written and verbal
A desire to work in a high-energy, focused, small-team environment with a sense of shared responsibility and shared reward
Interest in early research and development through to product roll-out in the fields of surgical AI and surgical robotics
Hands-on experience with ML frameworks, such as PyTorch, Tensorflow, or similar
Knowledgeable about MLOps platforms and/or ML CI/CD workflows to manage datasets and model training, deployment, and monitoring
Experience with MLOps tools like MLFlow, KubeFlow, W&B, etc
Knowledgeable about kubernetes
Experience with cloud compute environments such as AWS, GCP, etc
Experience with both edge and cloud deployments, focused on automation, scalability, and robustness
Experience with Python and SQL
Experience with Git e.g github, gitlab, bitbucket, etc
Ability to travel domestically and internationally (5-10%)

Integrating machine learning into digital products and services by working cross-functionally across engineering, data science, and machine learning teams
Developing automated workflows and tools to curate datasets and facilitate training of deep learning models
Working closely with Machine Learning and Data/Software Engineering teams to develop efficient processes for model development/deployment for various applications
Help support and manage a growing cloud infrastructure for MLOps