Machine Learning Engineer

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
• Support and manage a growing cloud infrastructure for MLOps

Qualifications

• 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
• 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%)