Senior Research Engineer - Enterprise Products

NVIDIA; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA seeks a Senior Research Engineer dedicated to Generative AI. This role involves developing and optimizing AI models and algorithms, collaborating with teams to integrate advanced solutions into products. The ideal candidate has extensive experience in Deep Learning frameworks and strong software engineering skills, primarily in C++ and Python.

Benefits

Equity

Benefits

Qualifications

• 8+ years of industry experience in Deep Learning frameworks.
• Strong computer science fundamentals.
• Experience mentoring junior engineers.

Responsibilities

• Develop new models focused on Large Language Models and Deep Learning.
• Design and implement distributed LLM inference systems.
• Mentor team members and ensure good engineering practices.

Skills

Deep Learning

Machine Learning

Natural Language Processing

C++

Python

Communication

Education

Bachelor's degree or equivalent experience

Tools

PyTorch

TensorFlow

CUDA

Job description

Senior Research Engineer - Enterprise Products

We are now looking for a Senior Research Engineer passionate about Generative AI inference. Are you excited to change the way people infuse AI into products and services? NVIDIA is at the forefront of generative AI models, from language to images. NVIDIA provides building blocks to democratize AI and make generative AI easy to develop, integrate, and deploy. Our team is dedicated to developing optimized inferencing technologies to support our growing generative AI needs. We contribute to all steps of the machine learning lifecycle: from conceptualization, to applied research, engineering for optimized inference, and deployment. Collaborate with research teams, engineers, and open-source community. Implement optimized LLM algorithms.

What you will be doing:

Developing new models and algorithms focused on Large Language Models, Natural Language Processing, and Deep Learning.

Design and implement multi-node serving architectures disaggregated serving and distributed LLM inference

Optimize multi-LoRA (and other PEFT technique) inference serving systems

Apply sophisticated quantization techniques (FP4/INT4, FP8) to reduce model footprint while preserving quality

Implement speculative decoding (draft target, eagle, medusa etc) and other latency optimization strategies

Demonstrating good engineering practices and mentoring other team members to do the same.

Collaborating with engineering teams across all of NVIDIA to ensure our software integrates seamlessly up and down the NVIDIA accelerated serving stack.

What we need to see:

Understanding of modern techniques in Machine Learning, Deep Neural Networks, Natural Language Processing, or Speech Recognition.

8+ years of industry experience in Deep Learning frameworks (PyTorch or TensorFlow).

Passion for software engineering, especially with excellent C++ and Python development skills, with meaningful contributions to major open-source projects.

Strong communication and interpersonal skills, along with the ability to work in a dynamic and distributed team. A history of mentoring junior engineers and interns is a huge plus.

Bachelor's degree or equivalent experience.

A desire to constantly grow and learn new things.

Strong computer science fundamentals - algorithms and data structures, computational complexity, parallel and distributed computing, system software.

Ways to stand out from a crowd:

Knowledge of CPU and/or GPU architecture.

GPU programming (CUDA).

We are now looking for a Senior Research Engineer passionate about Generative AI inference. Are you excited to change the way people infuse AI into products and services? NVIDIA is at the forefront of generative AI models, from language to images. NVIDIA provides building blocks to democratize AI and make generative AI easy to develop, integrate, and deploy. Our team is dedicated to developing optimized inferencing technologies to support our growing generative AI needs. We contribute to all steps of the machine learning lifecycle: from conceptualization, to applied research, engineering for optimized inference, and deployment. Collaborate with research teams, engineers, and open-source community. Implement optimized LLM algorithms.

What you will be doing:

• Developing new models and algorithms focused on Large Language Models, Natural Language Processing, and Deep Learning.

• Design and implement multi-node serving architectures disaggregated serving and distributed LLM inference

• Optimize multi-LoRA (and other PEFT technique) inference serving systems

• Apply sophisticated quantization techniques (FP4/INT4, FP8) to reduce model footprint while preserving quality

• Implement speculative decoding (draft target, eagle, medusa etc) and other latency optimization strategies

• Demonstrating good engineering practices and mentoring other team members to do the same.

• Collaborating with engineering teams across all of NVIDIA to ensure our software integrates seamlessly up and down the NVIDIA accelerated serving stack.

What we need to see:

• Understanding of modern techniques in Machine Learning, Deep Neural Networks, Natural Language Processing, or Speech Recognition.

• 8+ years of industry experience in Deep Learning frameworks (PyTorch or TensorFlow).

• Passion for software engineering, especially with excellent C++ and Python development skills, with meaningful contributions to major open-source projects.

• Strong communication and interpersonal skills, along with the ability to work in a dynamic and distributed team. A history of mentoring junior engineers and interns is a huge plus.

• Bachelor's degree or equivalent experience.

• A desire to constantly grow and learn new things.

• Strong computer science fundamentals - algorithms and data structures, computational complexity, parallel and distributed computing, system software.

Ways to stand out from a crowd:

• Experience architecting or developing large-scale distributed systems for deep learning.

• Knowledge of CPU and/or GPU architecture.

• GPU programming (CUDA).

The base salary range is 184,000 USD - 356,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.

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.

About the company

9637389 Nvidia Corporation is an American multinational technology company incorporated in Delaware and based in Santa Clara, California.

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