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're looking to grow our company, and build our teams with the smartest people in the world.
Our team is building the Data Platform that encompasses collection, processing, visualization, analysis, root cause detection, prediction models for both qualitative and quantitative data from millions of our end users. Our data sources include traditional personal computers, servers, mobile devices and distributed Web services. Our active projects include analysis for cloud gaming experience including streaming and launch experience, user behavior profiling, user base segmentation, actionable cluster identification, smart personalized recommendations and lifetime value analysis, capacity management and churn analysis. You will be adding intelligence and analysis capabilities to various user-facing projects, you will help to deliver the power of Data to our users across the world. Our technology stack relies on industry standard components (ELK, Tableau, Cassandra, Avro, Kafka, Aerospike, Redis, PostgreSQL, Python, R, etc) and proprietary tools implemented in Python, Java/Spring, JavaScript/NodeJS.
What You'll Be Doing
Build scalable algorithms for toolchains based on data processing and machine learning to root cause production issues.
Build domain knowledge of the product through the metrics, identify anomalies and data inconsistencies and help track those to resolution.
Develop frameworks for data ingestion and processing.
Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques.
Improve efficiency of the org by wrangling petabytes of data using cutting edge machine learning tools to provide actionable business and engineering insights.
What We Need To See
Pursuing MS or PhD in Data Science, Computer science, Operations Research, Statistics or related quantitative fields.
Strong background knowledge in Statistical Analysis.
Experienced in solving problems using machine learning techniques (clustering, classification, outlier analysis, etc) and deep learning models (Neural Networks).
Strong coding skills, including the ability to write readable, testable, maintainable and extensible code (primarily Python)
Experience with common tools for data storage and processing (e.g. Spark, Hadoop Map/Reduce, Hive, Cassandra) including drilling into problems of running large scale software in a big network.
Strong experience in data cleaning, aggregation, transformation and extraction.
Track record of analysis of time series data is a plus.
Experience in active ML production pipelines is a plus (MlFlow, KubeFlow).
Excellent interpersonal, presentation and reporting skills should be your strong sides.
Experience working on an Agile or iterative development team
Are you dedicated, upbeat and dynamic with excellent analytical ability? Are you an engineer who is hardworking and highly motivated about solving complex problems? If so, you may be a perfect fit for NVIDIA!
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.