Design and develop the GenAI open source Megatron Core and NeMo Framework
Solve large-scale, end-to-end AI training and inference challenges, spanning the full model lifecycle from initial orchestration, data pre-processing, and running of model training and tuning, to model deployment.
Work at the intersection of AI applications, libraries, frameworks, and the entire software stack.
Innovate and improve model architectures, distributed training algorithms, and model parallel paradigms.
Accelerate foundation model training and finetuning with mixed precision recipes and next-gen NVIDIA GPU architectures.
Performance tuning and optimizations of deep learning framework and software components.
Research, prototype, and develop robust and scalable AI tools and pipelines.

Requirements

MS, PhD or equivalent experience in Computer Science, AI, Applied Math, or related fields and 3+ years of industry experience.
Experience with AI Frameworks (e.g. PyTorch, JAX), and/or inference and deployment environments (e.g. TRTLLM, vLLM, SGLang).
Proficient in Python programming, software design, debugging, performance analysis, test design and documentation.
Consistent record of working effectively across multiple engineering initiatives and improving AI libraries with new innovations.
Strong understanding of AI/Deep-Learning fundamentals and their practical applications.

Benefits

Equity
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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonAI FrameworksPyTorchJAXTRTLLMvLLMSGLangdeep learningmodel trainingperformance tuning

Soft Skills

problem solvinginnovationcollaborationcommunicationdebuggingperformance analysistest designdocumentation

Certifications

MSPhD