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 @ 7
Communication @ 7
Data Engineering
Data Pipelines @ 7
Data Science @ 4
LLM
Machine Learning
Mentoring @ 6
Product Management @ 7
- 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
NVIDIA is developing AI and Accelerated Computing solutions for the Automotive industry. We are looking for a Senior Manager of Product to join our data team and lead a product group. Your core mission is to deeply understand what perception models need to improve — and translate that understanding into high-quality, high-value data annotation strategies that directly drive model performance gains.
This role sits at the intersection of perception research, data engineering, and labeling operations. You will work closely with perception scientists to identify model performance gaps, define annotation requirements, own the data roadmap, and drive end-to-end delivery across labeling vendors and internal teams. The best candidate combines strong product instincts with genuine technical depth in ML data pipelines and perception tasks.
Responsibilities
- Develop a deep understanding of how training data impacts perception model performance across tasks including 3D object detection, lane/road structure recognition, traffic sign and traffic light detection, and semantic segmentation.
- Partner with perception researchers and engineers to translate model capability gaps into concrete data requirements.
- Own annotation ontology design: define labeling taxonomies, attribute schemas, edge case handling rules, and inter-annotator consistency standards for perception network tasks such as 3D bounding boxes, lane elements, traffic sign/light classification and association.
- Anticipate how changes in data density, ROI size, and label complexity affect labeling throughput and delivery capacity; provide data-backed forecasts to stakeholders.
- Collaborate with global engineering and labeling teams to ensure data quality and explore how DNN/LLM/VLM improves the performance of data labeling.
Requirements
- BS degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience).
- 8+ years of product management experience, with at least 2+ years in a role directly involving ML/AI model development, data pipelines, or training data strategy.
- Genuine understanding of perception model fundamentals.
- Strong cross-functional communication skills.
- 3+ years of experience leading or mentoring a team of product managers, tech leads, or equivalent.
Benefits
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 25, 2026.