Senior Prediction and Planning Machine Learning Engineer - Autonomous Vehicles

NVIDIA is looking for an experienced Machine Learning Engineer to join its Autonomous Vehicle team in Santa Clara, CA, USA. As a member of our team you will develop key features for our autonomous driving platform. In this role, you will apply machine learning to a mix of prediction, planning, and control problems. You will create innovative ML solutions for NVIDIA’s next-generation automotive products. The candidate is required to have hands-on experience and deep knowledge in machine learning. Understanding of deep neural networks, autonomous vehicles, and domain adaptation is highly desirable. You are encouraged to work across people and project boundaries, and among computer vision, computer graphics, and machine learning approaches. You should have strong research, SW development, communication, interpersonal, and analytical skills. Join us and help craft the future of AI automation.

What you’ll be doing:

• Researching, implementing, and evaluating deep-learning-based methods for prediction and planning for NVIDIA's Autonomous Vehicle products.

• Designing, running, and analyzing experiments and testing to evaluate the efficiency of our solutions on real-world data.

• Partnering with system software engineering specialists to ship industrial strength ML models.

• Communicating and collaborating with multi-functional teams.

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.

• 5+ years of experience applying machine learning to address real-world problems.

• Excellent written and verbal communication skills and social skills.

• Strong Python programming experience with software design skills.

• Experience with deep neural network (DNN) training, inference and optimization in leading frameworks (Pytorch, Tensorflow, TensorRT, etc.).

• 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.

• Good communication and collaboration skills, as we work as a tightly knit team, always discussing and learning from each other.

Ways to stand out from the crowd:

Are you an enthusiastic contributor with a background that includes one or more of the following? If so, we want to hear from you!

• Experience in applying deep learning to prediction and planning for autonomous vehicles.

• You've worked in reinforcement learning or optimal-control.

• GPGPU programming (CUDA) experience.

• Published work for international relevant conferences (CVPR, NeurIPS, ICRA, etc).

Academic and commercial groups around the world are powering a revolution in AI using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing and autonomous vehicles. Intelligent AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an outstanding time. The era of AI has begun and NVIDIA is leading the way with revolutionary hardware and software. Come join us at NVIDIA!

The base salary range is 184,000 USD - 356,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.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.