Back
Tier-1 employer and Bangalore location increase competition, but senior, highly specialized ML performance requirements limit the candidate pool.
Deep ML model, framework, and hardware-performance focus makes background highly domain-specific.
Explicit 8+ years, advanced degree preference, and deep ML performance and framework expertise create strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Implement and optimize state-of-the-art machine learning models across diverse data domains and multiple ML frameworks.
Analyze, profile, and improve end-to-end performance of NVIDIA’s deep learning software and hardware stacks including unreleased hardware.
Collaborate cross-functionally to influence hardware/software roadmap and lead best practices for ML software development and release.
8+ years of experience in machine learning model implementation and software development.
MS or PhD in Computer Science, Computer Architecture, Mathematics, Physics, or related technical field, or equivalent experience.
Proficiency in Python and extensive knowledge of at least one ML framework (e.g., PyTorch, JAX, TensorFlow).
Experience with source control systems such as Git.
Deep experience working with ML model implementation on cutting-edge hardware and software platforms, including knowledge of GPU-accelerated computing.
Demonstrated ability to optimize ML workloads for performance, with grounding in algorithms and ML fundamentals.
Capable of collaborating with multidisciplinary teams to shape hardware/software co-design and enforce best practices in ML software engineering.