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SalaryNVIDIA is seeking deep learning research / engineering interns to join the AV perception research team. The team consists of a group of dynamic AI applied researchers and engineers and is committed to build industry-grade deep learning to take autonomous vehicle (AV) perception into production, we work on fundamental advances in scientific methods to enabling scaling-up the entire perception for the autonomous driving stack. We are looking for highly motivated individuals to work in the areas of deep learning, optimization and computer vision. Our interns have the unique opportunity to make algorithmic contributions to core products and apply their ideas at a very large scale. As an intern, you will conduct applied research related to one of the meaningful research topics mainly related to perception for autonomous driving. You may also have the opportunity to publish in premier conferences in the fields of Machine Learning and perception.
In order to scale-up current AI-algorithms, we need to learn from datasets orders of magnitude larger than existing ones which is a very challenging task. Our team at NVIDIA is dedicated to developing new algorithms to explore the vast amount of collected data to improve AI-based applications such as AV.
This includes research areas such as:
- Efficient data selection to improve learning and scaling-up training sets including active learning and mining strategies.
- Network interpretability to predict network failures and to design novel algorithms to continuously learn from data and from failures.
- Efficient training and inference to minimize training time and enable inference in embedded platforms.
- Synthetic to real domain adaptation.
To learn more about our high-level goals visit: https://atscaleconference.com/videos/scale-2018-keynote-inside-nvidias-ai-infrastructure-for-self-driving-cars/
What you'll be doing:
- You will be responsible for conducting applied research to advance the performance of our codebase applied to perception for autonomous vehicles. Research is done in areas related to large scale learning including semi-supervised deep learning, active learning, deep network architecture search, parameter optimization and modeling, domain adaptation, or life-long learning. You may have opportunities to influence the progress of the field by producing publications.
- Contribute to integrating novel algorithms into core applications to enable a better generation of autonomous vehicles, coding in Tensorflow to facilitate the integration into our codebase.
- Collaborate and increase the performance of existing perception-based systems for AV.
What we're looking for:
- Pursuing BS, MS, or Ph.D. in Computer Science, with a focus in Deep Learning, Artificial Intelligence or related fields.
- Expertise in Computer Vision and Deep Learning.
- Strong mathematical background and ability to analyze results.
- Excellent Tensorflow and python programming skills to bring ideas into production systems.
- A dedication to bring your work to completion and see your work having a worldwide impact.
- A self-motivated and good teammate with good communication and social skills.
- Publication or experience in fields related to machine learning, analytics, large-scale systems, statistics, and mathematics.
Ways to stand out from the crowd:
- Currently enrolled in a Ph.D. program in CS or Math.
- First author publications in top-tier peer-reviewed conferences such as NeurIPS, ECCV, ICML, CVPR, ICCV.
- Research or software engineering experience confirmed via internships, relevant work experience or code competitions.
The hourly rate for our interns is $19 - $93. Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.
You will also be eligible for Intern benefits.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
