Machine Learning Infrastructure Intern

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow, Deep Learning, Natural Language Processing (NLP)

Job Description

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.”

We are seeking outstanding engineers to bring GPU-accelerated machine learning to every data scientist on every cloud platform, and contribute to the RAPIDS open source software libraries. We're looking to grow our company, and build our teams with the smartest people in the world. Join us at the forefront of technological advancement! We're integrating RAPIDS with all the major cloud service providers and on-premise machine learning platforms. You will be working with specialists in GPU programming and AI infrastructure, to accelerate data science and improve performance and usability in these platforms. This internship is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA!

What you’ll be doing:

• Optimizing integration between RAPIDS machine learning libraries and cloud data analytics frameworks
• Developing reference architectures for large scale machine learning in the cloud
• Performance analysis and benchmarking
• Writing documentation and blogs to help others use these end-to-end solutions

What we need to see:

• Pursuing BS, MS, or PhD in Computer Science, Electrical/Computer Engineering or related fields
• Strong programming skills, especially in Python
• Strong problem-solving and debugging skills
• Background with major cloud computing services
• Familiarity with data analytics and machine learning concepts

Ways to stand out from the crowd:

• Familiarity with cloud architectures such as AWS, Azure, GCP
• Experience with C/C++ programming
• Background with building and deploying containers
• Experience with distributed computing platforms
• Familiarity with parallel programming

Are you dedicated, upbeat and dynamic with excellent analytical ability? Are you an engineer passionate and highly motivated about solving complex problems? If so, you may be a perfect fit for NVIDIA!