Work Flexibility: Remote

What You Will Do:

We are looking for an experienced and highly skilled Manager, AI Deployment. A successful candidate will be responsible for managing a cross-functional team of computer vision and AI engineers focused on deploying AI models and computer vision algorithms into new and existing medical device products. The team plays the crucial role of bringing AI-enabled products from the bench to the bedside and used by millions of patients each year.  This is a unique, high visibility opportunity for a technical leader who wants to manage a highly talented and energetic team of engineers to solve challenging computer vision and artificial intelligence problems to bring new innovations in AI to healthcare.

Responsibilities

• Execute a robust talent offense by attracting, developing, retaining, and engaging top talent while driving personal/professional growth of individuals, the team and delivering high quality results with passion, energy and drive
• Lead and mentor others in driving positive outcomes to technical, business, and personnel problems based through the application of problem-solving and process improvement methodologies
• Lead, mentor, formulate and work with the team to design, implement, evaluate, and optimize CV/DL/AI deployments as an integral part of AI-powered medical technologies
• Interface with a diverse group of stakeholders including business, product, marketing, regulatory and security leaders and project teams
• Create concise design documents and lead the team in making informed tradeoffs between model performance, latency, resource usage (memory/cpu/storage/IO), system architecture decisions
• Lead code reviews for projects/systems as an independent reviewer applying design principles, coding standards and best practices
• Guide the team through design control processes for product development that adhere to FDA guidance
• Promote a privacy and security first approach to software development and promote best practices in data management, data architecture, and data governance across teams and portfolio projects
• Ensure a robust strategy for automated building and testing while maintaining compatibility with supported platforms for both cloud and edge deployments

What You Will Need:

Required Qualifications:

• Bachelor's Degree in Computer Science, Software Engineering, Machine Learning, Electrical Engineering, Mathematics, Statistics, Bioengineering or related field
• 8+ years of work experience required
  · OR Master's Degree in the above fields and 6+ years of experience
  · OR PhD in above field(s) and 4+ years of experience

• 4+ years of experience in computer vision and deep learning / machine learning development and deployment

Preferred Qualifications:

• 2+ years of experience managing a team
• Experience optimizing inference pipelines on edge devices, e.g. those based on Nvidia GPU, etc.
• Experience working with libraries such as OpenCV, DLib, Tensorflow , TFlite, TensorRT, TorchScript, Boost C++ libraries for numerical computation, etc.
• Experience with deploying AI / ML models on Azure, GCP, and AWS clouds to achieve scalable deployment of AI / ML
• Familiarity with CV/ML frameworks such as PyTorch, OpenCV, PCL, TensorFlow, scikit-learn etc.
• Experience with medical devices and product development in a regulated industry, e.g., software developed under ISO 13485.

• $129k - $286k salary plus bonus eligible + benefits. Actual minimum and maximum may vary based on location. Individual pay is based on skills, experience, and other relevant factors.

Travel Percentage: 10%Stryker Corporation is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. Stryker is an EO employer – M/F/Veteran/Disability.Stryker Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.