Machine Learning Engineer

Intuitive • Peachtree Corners, GA

3d

About The Position

Role 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. Immediate projects and responsibilities may include: 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

Requirements

• 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%)

Nice To Haves

• Experience with successfully launching ML models into production
• Experience supporting large multi-modality dataset including image/video
• Experience within healthcare
• Experience with federated learning

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees