Senior Machine Learning Engineer

at Nvidia

USD 184,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 7 Communication @ 6 Computer Vision Data Pipelines Debugging @ 7 Deep Learning @ 7 Experimentation GPU @ 7 Machine Learning @ 7 PyTorch @ 7 Python @ 7 TensorFlow @ 7

Details

Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and interact with people are no longer science fiction. Today, a self-driving vehicle powered by AI can meander through a country road at night and find its way. NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots, and self-driving vehicles that can perceive and understand the world.

Our team is building the machine learning backbone of the Perception component for NVIDIA DRIVE AV. We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR & camera perception, multi-sensor fusion and AI infrastructure who are passionate about solving the hardest problems for self-driving cars. Are you interested in inventing human-level AI for perception under real world conditions? If so, join us!

Responsibilities

Model Development: Design, train, and optimize innovative machine learning models for LiDAR/camera perception and multi-sensor fusion (e.g., object detection/classification, image classification, semantic segmentation, tracking).
Develop and coordinate entire ML workflows, covering data pipelines, model training, model metrics, continuous performance instrumentation, and reporting.
Productization: Take ML models and algorithms from initial evaluation and experimentation all the way to product level on the NVIDIA DRIVE AV platform, developing highly efficient product code in C++.
Innovation: Keep track of the latest developments in machine learning, and incorporate techniques that improve platform performance.
Collaborate with LiDAR/camera teams, developers, engineers, and managers to turn complex ideas into reliable solutions for autonomous driving.

Requirements

MS or PhD in Computer Science, Engineering, or a related field, or equivalent experience.
8+ years of relevant proven industry experience applying machine learning to address real-world problems.
Strong C++ and Python programming and debugging skills with experience in developing for large, complex systems.
Deep practical experience applying machine learning to lidar/camera perception and multi-sensor fusion in automotive or related fields.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and a strong understanding of the mathematical foundations of ML.
Building and sustaining training and essential metric workflows for large-scale datasets.
Excellent communication and analytical skills. Self-motivated drive to solve hard problems.

Benefits

You will also be eligible for equity and benefits.

Additional information

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
Applications for this job will be accepted at least until July 14, 2026.