Machine Learning Engineer – Auto Labeling
| Company | 42dot |
|---|---|
| Location | Mountain View, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Senior |
Requirements
- Minimum of 5 years of relevant experience
- Master’s or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field relevant to machine learning, or equivalent experience
- Strong background in Linear Algebra, Probability, Signal Processing, and machine learning concepts
- Proficient programming skills in languages such as C/C++, Python, and others
Responsibilities
- Curating high-quality datasets tailored to autonomous driving scenarios and designing robust evaluation metrics to assess algorithm performance accurately
- Exploring techniques for efficiently selecting and labeling informative data points, minimizing labeling efforts while enhancing model performance
- Investigating methods for autonomously discovering optimal neural network architectures, specifically tailored for label generation from sensor and video data in autonomous driving contexts
- Developing strategies to leverage knowledge from related tasks or domains, addressing scenarios with limited labeled data (low-shot learning), and handling class distribution imbalances (long-tail learning) commonly found in autonomous driving datasets
- Optimizing learning algorithms and inference processes to ensure resource-efficient utilization, crucial for real-time deployment in autonomous driving systems
- Prioritizing the development of privacy-preserving techniques, ensuring the handling of sensitive data while maintaining high-performance label generation, in compliance with privacy regulations and safeguarding user information
Preferred Qualifications
- Experience in development related to autonomous driving and robotics, including Object Detection, Semantic Segmentation, Depth Estimation, and Transformer-based models
- Experience in building and utilizing automated learning pipeline systems
- Track record of publications or contributions in relevant fields, such as CVPR, ICCV, ECCV, NeurIPS, AAAI, etc.
- Enjoyment in discovering and solving new problems in the field