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Nvidia Senior Solutions Architect AdTech Media 
United States, Texas 
166605049

15.10.2025
US, CA, Remote
US, IL, Remote
US, NY, Remote
time type
Full time
posted on
Posted 28 Days Ago
job requisition id

What You'll Be Doing:

  • Partner with NVIDIA's engineering, product, and sales teams to secure design wins and drive the adoption of NVIDIA technology within the AdTech and Media distribution ecosystems.

  • Act as a trusted technical advisor for customers and partners, conducting proof-of-concept evaluations, and providing deep technical guidance on the best use of NVIDIA hardware and software.

  • Perform in-depth analysis and optimization of AI/ML models, recommender systems, and data processing pipelines to ensure peak performance on current- and next-generation GPU architectures.

  • Interact directly with customer data scientists, engineers, and developers on high-impact projects, using your expertise to help them deploy and scale their solutions.

  • Translate customer feedback into actionable insights for NVIDIA's product and engineering teams to help guide the development of new features and products.

  • Build technical collateral, such as notebooks, blogs, and presentations, that demonstrate the value of NVIDIA's platform for key use cases like real-time bidding, user personalization, and content recommendation.

What We Need To See:

  • BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related field (or equivalent experience).

  • 10+ years of experience as an ML/Software Engineer or Solutions Architect with a consistent record of writing production-level code in Python and/or C++.

  • Deep understanding of the AdTech, MarTech and Media distribution landscape, including key workflows, common platforms (e.g., DSPs, SSPs, CDPs), and the role of machine learning and data science.

  • Experience with ML/DL algorithms and frameworks such as PyTorch, TensorFlow, Spark, or Dask.

  • Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

  • A self-starter with a passion for continuous learning and a curiosity about solving sophisticated problems.

  • Proficiency in deploying ML/DL models at scale on public cloud platforms (e.g., AWS, GCP, Azure) or on-premise data center environments.

Ways To Stand Out From The Crowd:

  • Hands-on experience with NVIDIA GPU architectures and development tools like CUDA-X libraries (e.g., cuBLAS, cuDNN, RAPIDS).

  • Familiarity with MLOps technologies such as Docker, Kubernetes, and other cluster management software.

  • Knowledge of large-scale data processing and distributed systems.

  • Experience in a customer-facing role, successfully navigating complex technical conversations and building strong relationships.

  • A strong public profile (e.g., blogs, GitHub, conference talks) that demonstrates your expertise and passion for the field.

You will also be eligible for equity and .