Principal Data Scientist - Cloud Gaming and AI
$248k - $380k • Remote • US, CA, Santa Clara
Posted 1d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Join the NVIDIA GeForce NOW cloud team, responsible for delivering high-quality PC gaming experiences across various devices. This role focuses on building diagnostic, prescriptive, and AI-augmented analytics solutions, including real-time demand forecasting, capacity allocation, anomaly detection, and customer analytics. You will leverage data and AI to enhance cloud computing and streaming performance for millions of users, working with a technology stack that includes Python, Spark, SQL, Databricks, MLFlow, and Kubernetes.
Responsibilities
- Provide technical leadership to a team of Data Scientists and Engineers for global GPU compute services.
- Collaborate with leadership and stakeholders to define requirements, build roadmaps, and guide solution delivery.
- Lead the design, implementation, and deployment of AI/ML solutions for actionable insights and real-time prescriptive analytics.
- Build and deploy scalable solutions for user diagnostics, LLM chatbots, suspicious activity detection, and insight generation.
- Wrangle petabytes of data using statistical, AI/ML, and LLM models to provide real-time insights and improve organizational productivity.
- Utilize forecasting models and constraint optimization solvers for capacity management and server efficiency.
- Apply ML/AI predictive models with explainability for user retention/churn and campaign design.
- Develop multi-agent self-learning harnesses to enhance engineering productivity for analytics and deployments.
Requirements
- Master's/PhD or equivalent experience in Data Science, Statistics, Mathematics, Physics, Operations Research, or a related quantitative field.
- 15+ years of software experience in large-scale production deployments.
- 8+ years of proven experience in Statistics/AI/ML.
- Hands-on expertise in Python, SQL, Java, and modeling frameworks like Scikit-learn, PyTorch, TensorFlow for large projects.
- Experience with data storage and processing tools such as Spark, Pandas, and Delta Lake.
- Excellent verbal and written communication skills for conveying data insights to technical and non-technical stakeholders.
- Proven track record of successful past projects as a lead in data science research and application at scale.
- Experience with User Retention Modeling, LLMs, Time Series Forecasting, or Operations Research is a plus.
Benefits
- Equity
- Generous benefits package