NVIDIA's GeForce Now, the next-generation gaming service powered by NVIDIA GPUs in the cloud, transforms a Mac, any PC, or just a mobile device into a high-performance gaming rig. GeForce NOW automatically keeps games up-to-date, and users around the globe can instantly stream the latest games in high-definition resolution at the lowest latency for the smoothest of gameplay. Just click and play! Visit us at https://www.nvidia.com/en-us/geforce-now. In addition to gaming, we are growing our innovative low-latency streaming technology to a new range of applications, including augmented and virtual reality, artificial intelligence, and robotics.
We are looking for a Senior Software Engineer focusing on data analysis, machine learning, and AI to join a team of highly skilled and motivated engineers who help in redefining raw data into business-driving insights, developing advanced analytical models, and collaborating multi-functionally with engineering, product, and business teams. Now, are you passionate about driving this technology to its edge? Can you craft and Implement data analytic, machine learning and AI models to tackle real-world business challenges? Then, we are keen to hear from you.
What You’ll Be Doing
Analyze extensive structured and unstructured datasets to uncover trends, anomalies, and actionable insights.
Design, develop, and deploy machine learning and AI models to tackle real-world business challenges.
Build robust data pipelines and analytics dashboards to support data-driven decisions across teams.
Mentor and provide technical guidance to team members on standard processes for data science and methodologies.
Work with collaborators to gather requirements, define problem statements, and convert business needs into technical solutions.
Communicate complex results to technical and non-technical audiences through presentations, reports, and visualizations.
Ensure the quality, integrity, and security of data throughout analytical processes.
Identify and implement opportunities for continuous process and system improvement within the analytics function.
What We Need to See
Bachelor’s or Master’s degree in Computer Science or closely related field, or equivalent experience will be considered.
7+ years of hands-on experience in data analysis, preferably with exposure to large-scale datasets.
Strong proficiency in Python and experience with data analysis and visualization libraries (e.g., pandas, NumPy, matplotlib, seaborn).
Shown proficiency with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and model lifecycle from development to deployment.
Proven grounding in statistics, regression, classification, clustering, and related analytical methods.
Knowledge of SQL and experience with large-scale data extraction and manipulation.
Ability to quickly gain domain knowledge and apply analytical skills within that context.
Outstanding communication, documentation, and interpersonal skills; ability to work effectively in a multi-functional, globally distributed team.
Strong analytical thinking, problem-solving abilities, and a proactive, self-motivated approach.
Ways to Stand Out from the Crowd
Proficient in data analysis of extensive datasets.
Familiar with global low-latency cloud based streaming services and their networking challenges
Proven experience in C++ software development, optimization, and debugging.
Knowledge in the computer networking or WiFi networks.
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What We Do
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, NVIDIA is increasingly known as “the AI computing company.”
