Sr. Director, Program Management

OXOS Medical, Inc. empowers every provider with the capability, clarity, and confidence to make accurate decisions at the point of care. We are building new kinds of radiographic imaging devices that push the boundaries of previous solutions by improving image quality, reducing radiation exposure, improving ease of use, and building solutions to deliver care outside of traditional scenarios. We enable anyone anywhere to access radiologic diagnostics at the point of need, expanding availability and changing how healthcare is delivered.

OXOS Medical is constantly innovating, building on our best-in-class imaging device, and expanding into cloud-based imaging platforms, robotic guided imaging, intraoperative computed tomography, and telemedical solutions. OXOS Medical has raised $26M from prominent MedTech investors, venture capital firms, and renowned orthopedic surgeons.

OXOS is searching for a Machine Learning Engineer to join our high-growth company. You will join a dynamic team of passionate people who work daily to change how radiographic diagnostics are delivered. OXOS’ mission is to increase access and availability using the world’s first handheld Dynamic Digital Radiography Device. OXOS uses computer vision to guide users in proper patient positioning, automatically determine imaging techniques, and assess image exposure and anatomy positioning. These technologies are in their infancy, and the ML Engineer will refine and advance them to minimize radiation dose, decrease reshoot rates, and eliminate specialized training requirements.

Responsibilities

As the Machine Learning Engineer, your core duties will be to: 

• Design, build, deploy, and improve machine learning models, for computer vision and structured data problems.
• Architect, implement, and integrate efficient ML systems to perform batch or online inference on edge.
• Implement robust monitoring systems to detect and report training-serving skew.
• Research and document regulatory compliance strategies for applicable projects.
• Review existing and future ML implementations for adherence to best practices.
• Implement optimizations to existing ML models for performance, inference speed, and explainability.
• Transition production-ready models to production-grade training pipelines on Google Cloud Platform

Qualifications and Skills

• Bachelor’s Degree or higher in Computer Science or related field.
• Proficiency in Python 3, TensorFlow, and Git are must-have skills.
• Comfortable running PyTorch training code.
• Familiarity with writing and compiling C++ code.
• Familiarity with CMake.
• Excellent communication skills, including the ability to clearly and effectively communicate technical information to team members, stakeholders, and vendors.

Benefits and Perks

• Health, Dental, and Vision Insurance
• 401(k)
• Competitive pay and equity in the company
• The opportunity to work with an innovative, early-stage company that is changing medical imaging as we know it  
• Endless opportunities for growth and development