Manager, AI Deployment

The Manager, AI Deployment at Stryker Corporation is tasked with leading a cross-functional team of computer vision and AI engineers. Responsibilities include managing AI model deployments, mentoring team members, interfacing with stakeholders across multiple departments, and ensuring compliance with FDA regulations. The role also emphasizes creating design documents and guiding the team through design control processes, all while promoting a focus on security and privacy in software development.

To qualify for the Manager, AI Deployment role at Stryker Corporation, candidates must have a Bachelor's Degree in Computer Science, Software Engineering, or related fields, along with at least 8 years of relevant experience or a higher degree with appropriate experience. Specific expertise in computer vision, deep learning, and machine learning is essential, alongside managerial experience and familiarity with medical device development.

In the Manager, AI Deployment position at Stryker Corporation, you will be instrumental in transforming innovative AI technologies into practical applications for medical devices. By leading a skilled team, you'll help solve complex challenges in computer vision and artificial intelligence, ultimately bringing sophisticated AI solutions to patients at the bedside. Your strategic direction can significantly enhance healthcare by improving the capability and efficiency of medical devices.

The Manager, AI Deployment at Stryker Corporation will work with a range of cutting-edge tools and technologies, including libraries such as OpenCV, TensorFlow, and PyTorch for AI and machine learning development. Additionally, experience with cloud platforms like Azure, GCP, and AWS is crucial for deploying models smoothly. Proficiency in optimizing inference pipelines on devices like Nvidia GPUs is also highly beneficial.

This position offers robust career growth opportunities at Stryker Corporation. As a Manager, you will not only refine your technical expertise but also enhance your leadership skills by guiding and mentoring a talented team of engineers. Your efforts in driving innovation in AI technology can lead to advancement within the organization, potentially paving the way to higher leadership roles within the company.

In interviews for the Manager, AI Deployment role at Stryker Corporation, discuss specific projects where you successfully implemented AI models in medical devices. Highlight any challenges faced, such as regulatory compliance or integration with existing systems, and explain how you overcame them. Show your understanding of the impact this work has on patient care.

When asked about mentoring, explain your philosophy of fostering an inclusive environment where team members feel comfortable sharing ideas. Discuss how you support their growth by providing constructive feedback, encouraging continuous learning, and establishing clear goals for their professional development.

Talk about using project management tools and methodologies to effectively prioritize tasks. Explain how communication with your team and stakeholders is key in keeping everyone aligned on priorities. Sharing specific examples of juggling deadlines while maintaining quality demonstrates your capability in this area.

In your response, discuss the importance of code quality and adherence to coding standards. Describe your process for conducting thorough but efficient code reviews, focusing on design principles, readability, and testing. Mention any tools you use for code management to streamline this process.

Select a specific technical challenge relevant to computer vision or AI. Describe the problem clearly, your thought process in tackling it, the solutions you considered, and ultimately the successful approach you implemented. Emphasize teamwork and any collaborative efforts involved in reaching a resolution.

When discussing your experience with FDA regulations, detail your understanding of the importance of compliance in the development of medical technologies. Provide examples of how you've navigated design controls, risk management, and documentation to ensure adherence to regulatory guidance in past projects.

Respond by describing your familiarity with the specific constraints of edge devices and the optimization techniques you've used, such as model pruning, quantization, or using lightweight frameworks. Cite any successful projects where you reduced latency or resource usage while maintaining model accuracy.

Discuss the significance of creating open lines of communication and how you encourage sharing diverse perspectives in team meetings. Highlight previous successes where you facilitated teamwork across functionally diverse groups, leading to innovative solutions and improved project outcomes.

Describe your commitment to continuous learning through professional networks, relevant literature, and attending industry conferences. Mention how you apply this newfound knowledge to your team and projects, ensuring you remain at the forefront of technological advancements in the field.

Share your insights on emerging trends, such as personalized medicine, predictive analytics, and AI's role in remote monitoring. Discuss how these trends influence deployment strategies and impact patient outcomes, showcasing your expertise in future developments in the AI healthcare landscape.