About the job
Join our global Developer Technology (DevTech) team at NVIDIA, where we drive innovation and enhance the value of our platforms for developers. As a key member of our AI DevTech team, you'll lead a team of highly skilled engineers accelerating end-to-end performance of real-world Deep Learning and Machine Learning applications and developing novel algorithms to optimally leverage Nvidia hardware. Application examples are Large Language Models (LLMs), Computer Vision, Speech, Recommender Systems, and Multimodal architectures. As a Developer Technology Manager, you'll define and lead strategic technical initiatives, setting short- and long-term goals for your team. You'll work closely with customers as well as NVIDIA Research, hardware, and software teams to drive innovation and advance the state-of-the-art in accelerated Deep Learning and Machine Learning. Your team will focus on optimizing performance of complex parallel algorithms and workloads on NVIDIA platforms, including GPU, CPU, and interconnects.
Responsibilities
Lead your team to optimize and develop algorithms for Machine Learning and Deep Learning applications
Define and drive technical initiatives to advance the state-of-the-art in accelerated Deep Learning and Machine Learning applications
Collaborate with research, hardware, and software teams to influence the design of next-generation hardware, software, and programming models
Develop and communicate technical solutions to external and internal collaborators, including technical design decisions and project plans
Hire the best talent to join your team, promoting a diverse and skilled team that can tackle complex technical challenges
Coach and grow your team, promoting a culture of engineering excellence and idea proliferation
Qualifications
Minimum
An MS or PhD in Computer Science, Computer Engineering, or in a related computationally focused science or engineering degree (or equivalent experience).
8+ overall years of relevant experience with 5+ years in a technical role and 3+ years of experience in an engineering leadership role.
In-depth expertise in linear algebra and performance optimization of Deep Learning training and inference
Background in parallel programming, e.g., CUDA, OpenMP, MPI, pthreads, etc.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
Knowledge of CPU and GPU architecture fundamentals and low-level performance optimizations
Excellent written and presentation skills.
Proven track record of planning and leading critical initiatives.
Preferred
A PhD in a relevant field
Expertise in LLMs, multimodal model architecture and performance optimizations of relevant computational primitives
Proven experience with recruiting top talent.