Senior TPM - GPU-Accelerated Data Science Platforms (Equity)

NVIDIA Corporation; California (MO); Hybrid; USD 168,000 - 258,750; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in the Analytics & Data Intelligence team seeks a Senior Program Manager to own planning and execution for GPU-accelerated data science libraries, balancing long-term strategy with near-term priorities and defining scope, milestones, and metrics.

You will drive cross-functional collaboration across engineering, product, marketing, and the open-source community, lead releases, security, and compliance programs, and build dashboards to measure release health and impact.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field—or equivalent experience.
• 8+ years of technical program management experience leading complex software initiatives in data science, data processing, accelerated computing, high-dimensional search, self-directed AI, or closely related domains.
• Strong technical foundation with experience as an engineer, data scientist, or senior technical program leader; familiarity with open-source software development and PyData ecosystem.

Responsibilities

• Own planning and execution for NVIDIA’s GPU-accelerated data science and data processing libraries, building integrated roadmaps with milestones and success metrics.
• Drive cross-functional execution across engineering, product, marketing, go-to-market teams, and the open-source community; manage dependencies and releases.
• Lead software release, security, and compliance programs while improving development processes and delivery practices.
• Build and maintain program metrics to measure release health, quality, and adoption; use data to drive decisions.

Skills

Python

C++

Data science

GPU-accelerated computing

Education

Bachelor’s degree in Computer Science or Engineering

Job description

NVIDIA Corporation in the Analytics & Data Intelligence team seeks a Senior Program Manager to own planning and execution for GPU-accelerated data science libraries, balancing long-term strategy with near-term priorities and defining scope, milestones, and metrics.

You will drive cross-functional collaboration across engineering, product, marketing, and the open-source community, lead releases, security, and compliance programs, and build dashboards to measure release health and impact.