About the role
NVIDIA is looking for engineers for our core AI Frameworks (Megatron Core and NeMo Framework) team to design, develop and optimize diverse real world workloads. Megatron Core and NeMo Framework are open-source, scalable and cloud-native frameworks built for researchers and developers working on Large Language Models (LLM) and Multimodal (MM) foundation model pretraining and post-training. Our GenAI Frameworks provide end-to-end model training, including pretraining, reasoning, alignment, customization, evaluation, deployment and tooling to optimize performance and user experience.
In this critical role, you will expand Megatron Core and NeMo Framework's capabilities, enabling users to develop, train, and optimize models by designing and implementing the latest in distributed training algorithms, model parallel paradigms, model optimizations, defining robust APIs, meticulously analyzing and tuning performance, and expanding our toolkits and libraries to be more comprehensive and coherent. You will collaborate with internal partners, users, and members of the open source community to analyze, design, and implement highly optimized solutions.
What you’ll be doing:
Develop algorithms for AI/DL, data analytics, machine learning, or scientific computing
Contribute and advance open source NeMo-RL, Megatron Core, 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.
What we need to see:
MS, PhD or equivalent experience in Computer Science, AI, Applied Math, or related fields.
5+ years of industry experience.
Experience with AI Frameworks (e.g. PyTorch, JAX, Ray), 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.
Ways to stand out from the crowd:
Hands-on experience in large-scale AI training, with a deep understanding of core compute system concepts (such as latency/throughput bottlenecks, pipelining, and multiprocessing) and demonstrated excellence in related performance analysis and tuning.
Prior experience with Reinforcement Learning algorithms and compute patterns
Expertise in distributed computing, model parallelism, and mixed precision training
Prior experience with Generative AI techniques applied to LLM and Multi-Modal learning (Text, Image, and Video).
Knowledge of GPU/CPU architecture and related numerical software.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearningSkills & Tags
Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
Similar roles
Principal Algorithm Engineer – Imaging / Ultrasound (ML)
Medtronic
Principal Software Engineer - Signals & Algorithm Interfaces (Python/C++)
Medtronic
Principal Deep Learning Algorithm Engineer
NVIDIA
Principal AI/ ML Algorithm Development Engineer - Battery Insights
Analog Devices
Algorithm Engineer
KLA Corporation
Senior Lead Engineer, Imaging Algorithm Development - RDT Biometrics and Clinical Evidence
Roche