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What you will be doing:
Lead both technically and managerially for the CUDA teams creating a ‘delightful Pythonic CUDA developer experience: build vision, strategy, and feature roadmaps.
Develop strategic direction for the group and foster software quality improvement for CUDA Python stack deployed on multi-GPU products/systems.
Thrive in a highly dynamic and diverse environment, showing strong interpersonal skills, insightful organizational and exceptional communication abilities, and a real passion for working as a single focused team.
Continuously review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are performing in the most efficient and transparent manner.
Collaborate with peer engineering teams, program and product management, and partners to ensure product requirements, goals and objectives are met and exceeded.
Highly resilient; pursues every task with drive and a sense of urgency.
Knowledge/skills to stay on top of the latest Python developer trends & technologies, and be able to internalize and communicate how new technologies can be integrated into NVIDIA’s Python ecosystem.
Act as a player-coach and are not be afraid of rolling up your sleeves and jumping into details.
You are passionate about mentoring, developing, and motivating a high-performing team to drive impact.
What we need to see:
MS, or Ph.D. in CS, EE (related technical field) or equivalent experience
15+ overall years of experience in the software industry. 8+ years in strong technical leadership positions (technical director, architect). 5+ years as Director of engineering level management
A ‘Python developer at heart’ with a solid understanding of Python syntax, semantics, data structures, and object-oriented programming.
Deep familiarity with Python developer eco-system and prior experience of developing Python libraries or contributing to popular frameworks.
Success leading complex software products through the full product life cycle (definition, development, delivery, maintenance/support, end-of-life) in Agile environment.
Prior familiarity with GPU compute programming model frameworks such as CUDA, NVIDIA RAPIDS is a plus
You will also be eligible for equity and .
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