System Software Engineer, Python and C/C++ - Deep Learning

at  NVIDIA

NVIDIA is hiring system engineers for its Deep Learning Algorithms team. Academic and commercial groups around the world are using GPUs to redefine deep learning and data analytics, and to power data centers. Join the team building software which will be used by the entire world. Work with the scientific community to implement the latest AI solutions. Ability to work in a dynamic, fast-paced environment is required as well as strong interpersonal skills.
In this role you will be interacting with internal partners, users, and members of the open source community to analyze, define and implement highly optimized solutions. The scope of these efforts includes a combination of crafting and implementing new solutions, defining APIs, performance tuning and analysis, analyzing functionality coverage across multiple solutions, build larger, coherent AI toolset. Are you ready for this challenge?

WHAT WE NEED TO SEE:

• Excellent Python and C/C++ programming knowledge
• 8+ years of work experience in software development
• Experience in design and implementation of sophisticated systems with decoupled dependencies
• Knowledge of design patterns and software engineering principles
• Strong analytical skill, knowledge about algorithms and data structures
• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects
• Good communication and documentation habits
  NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking people in the world working for us. If you’re creative and autonomous, we want to hear from you! We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

• Research, prototype, develop and optimize solutions, tools and libraries for deep learning, data analytics, machine learning, or scientific computing
• Analyse, influence and improve deep learning libraries and frameworks standards and APIs according to good engineering practices
• Collaborate with team members and other partners