VP, Software Engineering presso Precision Neuroscience
Precision Neuroscience · Santa Clara, Stati Uniti d'America · Hybrid
- Senior
 - Ufficio in Santa Clara
 
Key Responsibilities
- Oversee all Software Engineering projects and initiatives, ensuring our products are safe, effective, and secure, and delivered on time and on budget
 - Define the overall software development practices that support high-quality and timely delivery of Precision’s software roadmap
 - Successfully partner across the organization, particularly with device hardware and ML R&D teams, to achieve overall company objectives
 - Review technical designs and sign-off on development plans for key software initiatives, especially those involving device integration and the implementation of ML algorithms
 - Communicate effectively to both technical and non-technical audiences to ensure alignment with software team goals, milestones, and risks
 - Build and grow a high-performing software organization through hiring, developing people, and creating a strong team culture that retains key talent
 
Skills, Knowledge and Expertise
- 15+ years’ experience in software development in a medical device environment (preferably Class III), including 10+ years’ experience as a director or above
 - Bachelor’s degree or above in computer science, ECE or related field
 - Proven track record of building and scaling high-performing teams supporting full life-cycle software development through commercialization
 - Experience in developing a scalable systems architecture that supports cross-platform software development including desktop, mobile and cloud environments
 - Experience interfacing with embedded systems teams and supporting software-hardware integration
 - Knowledge and application of medical device software development standards, such as IEC 62304, and FDA guidance on software development, usability and cybersecurity
 - Successful track-record of working in fast-paced and interdisciplinary engineering teams
 - Strong experience collaborating with Quality and Regulatory working groups preferred
 - Familiarity with modern machine learning concepts and collaboration with ML R&D teams is a plus