Develop algorithms for AI/DL, data analytics, machine learning, or scientific computing
Contribute and advance 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, running of model training and tuning, to model deployment.
Work at the intersection of compter-architecture, libraries, frameworks, AI applications and the entire software stack.
Innovate and improve model architectures, distributed training algorithms, and model parallel paradigms.
Performance tuning and optimizations, model training and finetuning with mixed precision recipes on next-gen NVIDIA GPU architectures.
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 field and 5+ 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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

algorithmsAIdeep learningdata analyticsmachine learningscientific computingperformance tuningmodel trainingmodel deploymentPython

Soft Skills

problem solvinginnovationcollaborationcommunicationeffective working

Certifications

MSPhD