About the job
We are looking for a talented individual to join our growing machine learning and data science team to help provide creative ways to develop new technology focused on surgical workflow and performance for next generation robotic surgery platforms. As a Machine Learning Engineer, you will work at the intersection of machine learning and engineering (i.e., MLOps) to contribute to innovative digital solutions leveraging Surgical AI/ML technologies.
Responsibilities
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
Qualifications
Minimum
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 (Domino Data Labs) 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%)
Preferred
Experience with successfully launching ML models into production
Experience supporting large multi-modality dataset including image/video
Experience within healthcare
Experience with federated learning