Machine Learning Engineer
: Job Details :

Job Description

Primary Function of Position:

Are you passionate about designing software solutions that enable complex user interfaces and user interactions? We are looking for someone who thrives in a collaborative product development environment and wants to push the boundaries of what is possible in surgical robotics today! Join our team of passionate and dedicated software, computer vision and machine learning engineers to develop real-time sensing and perception technologies that support complex human machine interfaces for next- generation robot-assisted surgery platforms.

The successful candidate must excel in a high-energy, focused, small-team environment, and must have a solid track record of taking machine learning, deep learning, and computer vision technologies to product. A sound sense of mutual responsibility and shared reward is required.

As part of the User Interaction Algorithms team, immediate responsibilities include:

• Participate in the design, development, and optimization of computer vision and machine learning based solutions for state-of-the-art user interfaces
• Support tools to facilitate machine learning pipelines and automated workflows
• Test and maintain large databases of surgical video, system data, and meta data
• Work closely with research data scientists throughout analysis, visualization, and modeling efforts

• Develop tools and methods for rigorous testing of algorithms prior to product launch
• Play a central role in putting models into production and developing tools to monitor product performance in the field
• Support multiple engineering and analytics teams in collecting, accessing, and analyzing data

Additional responsibilities include:

• Study and improve algorithm performance metrics that correlate with user experience, and that can be used to drive continuous improvement
• Keep current with our software/hardware development efforts and understand overall trends in AI, ML and Cloud technologies
• Continuously explore optimal data coverage for various use cases