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What You Will Be Doing:
Play meaningful role in NVIDIA's effort in contributing to JAX.
Design and implement JAX core components and drive peak performance on NVIDIA products.
Work with AI applied researchers and leaders to build future-proof models
Build tools that will increase the efficiency of teams developing AI-based systems.
Work to bridge the gap between the latest in numerical computing, simulation and deep learning research and their applications in real world products.
What We Need To See:
BS in Computer Science or Computer Engineering or related field (or equivalent experience)
5+ years relevant experience
C/C++ and Python programming
Experience with machine learning frameworks and their internals (e.g. PyTorch, TensorFlow, scikit-learn, etc.)
Proven ability developing customer-facing solutions, balancing feature requests and bugs.
Proven technical foundation in CPU and GPU architectures, numeric libraries, modular software design.
Highly motivated with excellent verbal and written communication skills.
Ability to work successfully with multi-functional teams, principles and architects. Coordinates effectively across organizational boundaries and geographies.
Ways To Stand Out From The Crowd:
Understanding of JAX, Autograd, tracing, code generation and DSL compilers and their design.
Understanding of deep learning training in distributed contexts: multi-GPU, multi-node, synchronous vs asynchronous.
Background with software shipping cycles (dev, deploy, release, CI).
Experience building distributed systems and services at large scale.
You will also be eligible for equity and .
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