NVIDIA

You will apply machine learning to Autonomous Vehicle perception, to develop features for our next generation autonomous driving platform.. You will be challenged to improve robustness and accuracy of obstacle perception DNN models using multiple sensor modalities (e.g., camera, radar, and lidar) under challenging and diverse scenarios to fully enable autonomous driving anywhere and anytime.. Delving into the thrilling sphere of deep learning, conducting research and implementing methods for real-time perception tasks and planning in the context of autonomous driving.. Applied Experience in AV: Evidence of practical experiments and projects within the autonomous driving domain.. Research Experience: Relevant published research, particularly in relation to perception tasks for autonomous driving, general computer vision and machine learning.

senior machine learning engineer

We are looking for an experienced Machine Learning Engineer to join our team. You will apply machine learning to Autonomous Vehicle perception, to develop features for our next generation autonomous driving platform. As a member of our perception team, you will build world-class obstacle perception solutions by developing groundbreaking deep learning/machine learning models using large-scale data. You will be challenged to improve robustness and accuracy of obstacle perception DNN models using multiple sensor modalities (e.g., camera, radar, and lidar) under challenging and diverse scenarios to fully enable autonomous driving anywhere and anytime. What You'll Be Doing Team work: Foster close collaborations with our researchers and engineers, transforming innovative research into our autonomous driving platform.
Exploration: Deep Learning research, implementation, and innovation. Delving into the thrilling sphere of deep learning, conducting research and implementing methods for real-time perception tasks and planning in the context of autonomous driving. Continuously look out and keep track of the latest developments in machine learning and autonomous driving, incorporating new methodologies, technologies, and solutions that could improve our system's performance and capabilities.
Experimentation: Design and implement experiments, analyzing the results to assess the effectiveness of our solutions. This vital task involves manipulating real-world data and providing insightful findings that directly influence our technology's performance.
Documentation: Thoroughly document methodologies, insights, and results to facilitate knowledge sharing, future development and reproducibility. What We Need To See MS or PhD level education in Engineering or Computer Science with a focus on Deep Learning, Artificial Intelligence, or a related field, or equivalent experience.
Excellent written and verbal communication skills and strong social skills.
5+ years of practical experience applying machine learning to address real-world problems
Strong Python programming experience with software design skills.
Experience with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, Tensorflow, TensorRT)
Practical software engineering experience, developing for large and complex systems.
Excellent understanding of the mathematical foundations of machine learning and deep learning
Self-motivation combined with team spirit and the urge to learn new things and solve hard problems. Ways To Stand Out From The Crowd Applied Experience in AV: Evidence of practical experiments and projects within the autonomous driving domain. Experience in delivering features to AV stacks or related products..
Research Experience: Relevant published research, particularly in relation to perception tasks for autonomous driving, general computer vision and machine learning. Track record of winning AV-related challenges or producing SOTA results on benchmarks and leaderboards.
Advanced Model Knowledge: Experience working with Transformers and other visual recognition models, especially models for 2d/3d object detection and tracking. Familiarity with bird's eye view perception solutions and techniques, and familiarity with common toolkits and libraries such as MMDetection3D.
Cross-functional Collaborator and Problem Solver.
Adaptable Learner: Evidence of continual learning and skill development in the rapidly evolving field of machine learning and AI. This might include further education, certifications, or a consistent practice of self-learning. Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. The base salary range is 144,000 USD - 333,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis. 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. #J-18808-Ljbffr

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