Senior Machine Learning Engineer, Perception - Autonomous Driving
at Nvidia
USD 184,000-356,500 per year
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Python @ 7
Algorithms @ 7
Leadership @ 7
Communication @ 4
Prioritization @ 4
Technical Leadership @ 7
PyTorch @ 6
GPU @ 4
Deep Learning @ 4
AI @ 4
Robotics @ 4
- 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.
Details
Intelligent machines powered by Artificial Intelligence are enabling computers that can learn, reason and interact with people. GPU deep learning provides the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run deep learning algorithms that act as the brain of computers, robots and self-driving cars that can perceive and understand the world.
As a member of the Perception team you will develop and productize NVIDIA's autonomous driving solutions. You will drive end-to-end solutions for perception modules responsible for online mapping — including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. The role focuses on improving robustness, accuracy, and efficiency of perception solutions to enable autonomous driving anywhere and anytime.
Responsibilities
- Design end-to-end solutions for perception and the AV stack to enable road network detections across varied driving environments (complex intersections, rural curvy roads, multi-level highways).
- Conduct applied research and development of deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.
- Develop generalizable approaches to support diverse ODDs (operational design domains) and country/region expansion.
- Drive and prioritize data-driven development by collaborating with large data collection and labeling teams: data collection prioritization and planning, labeling prioritization, and labeling efficiency optimization.
- Leverage data simulation and augmentation to handle extreme scenarios.
- Productize perception solutions to meet product requirements for safety, latency, and software robustness.
Requirements
- Minimum requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
- 2+ years of technical leadership demonstrating high technical and organizational complexity is a strong plus.
- Hands-on experience developing deep learning and algorithms to solve real-world problems; proficiency with deep learning frameworks (e.g., PyTorch).
- Experience in data-driven development and collaboration with data and ground-truth teams.
- Strong programming skills in Python and/or C++.
- Outstanding communication and teamwork skills.
Ways to Stand Out
- Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras.
- Hands-on experience developing and deploying DNN-based solutions to embedded platforms for real-time applications.
- Technical publications in leading conferences/journals demonstrating expertise in deep learning.
- Experience with Transformers, BEV architectures, and modern static-world perception techniques. Experience on online mapping and complex road detection problems is a big plus.
Compensation & Benefits
- Base salary range:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- You will also be eligible for equity and benefits (link provided in original posting).
Additional Information
- Applications for this job will be accepted at least until June 8, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.