Senior Deep Learning Engineering - Autonomous...

NVIDIA Ltd.
Santa Clara, CA, United States
15 days ago
Apply on www.juju.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$224,000.0
Working hours
Regular working hours
Job source

Tech stack

Computer Engineering High-Level Architecture Python (Programming Language) Machine Learning Pytorch Large Language Models Deep Learning Information Technology Machine Learning Operations

Requirements

  • Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience)

  • 10+ years of professional experience in deep learning or applied machine learning.

  • Strong foundation in deep learning algorithms, including hands-on experience with LLMs and VLMs

  • Deep understanding of general transformer architectures, inference bottlenecks, and popular model architectures such Qwen family.

  • Proficient in building and deploying models using PyTorch in production-grade environments.

  • Solid programming skills in Python

Ways to stand out from the crowd:

  • Proven experience deploying LLMs or VLMs at scale in real-world applications using vLLM, SGLang.

  • Hands-on experience with SFT, DPO, GRPO techniques for fine-tuning

  • Proven experience in developing image and video search solutions at scale.

Benefits & conditions

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

About the company

NVIDIA (Santa Clara, CA)

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology-and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

At NVIDIA, we’re building the future of autonomous driving - from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: Data. Extensive, diverse, high-quality data. We are seeking a highly skilled Deep Learning Engineer to develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world’s most advanced AI platforms. We are looking for hands-on experience training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments. You will collaborate with other researchers, software engineers to bring pioneering AI models from prototype to production.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

3:51 min

Overcoming hardware configuration barriers in machine learning

Jose Luis Latorre Millas · LIVE

2:15 min

Open-source community and machine learning frameworks

Gian Marco Iodice Gian Marco Iodice · World Congress 2025

Videos

See all

Related articles

See all