Senior Solutions Architect, AdTech and Media

Details

The NVIDIA Solutions Architect team seeks a senior-level, hands-on Solutions Architect to collaborate with the world's most innovative companies in the AdTech and Media distribution space. You will work with top minds in the industry, helping them accelerate their workflows and solve complex business challenges with NVIDIA's full-stack accelerated computing platform. The role is focused on technical customer engagement, performance optimization of ML/AI workloads on GPUs, and driving adoption of NVIDIA hardware and software within AdTech and media distribution ecosystems.

Responsibilities

• Partner with NVIDIA engineering, product, and sales teams to secure design wins and drive adoption of NVIDIA technology within AdTech and media distribution ecosystems.
• Act as a trusted technical advisor for customers and partners; conduct proof-of-concept evaluations and provide deep technical guidance on 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 to help them deploy and scale solutions.
• Translate customer feedback into actionable insights for NVIDIA product and engineering teams to guide new features and products.
• Build technical collateral (notebooks, blogs, presentations) demonstrating NVIDIA platform value for use cases like real-time bidding, user personalization, and content recommendation.

Requirements

• 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 and 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.
• Proficiency in deploying ML/DL models at scale on public cloud platforms (AWS, GCP, Azure) or on-premise data center environments.
• Excellent communication and presentation skills; ability to articulate complex technical concepts to technical and non-technical audiences.
• Self-starter with passion for continuous learning and curiosity for solving sophisticated problems.

Ways to Stand Out

• Hands-on experience with NVIDIA GPU architectures and development tools such as CUDA-X libraries (cuBLAS, cuDNN, RAPIDS).
• Familiarity with MLOps technologies like Docker, Kubernetes, and other cluster management software.
• Knowledge of large-scale data processing and distributed systems.
• Experience in customer-facing roles, navigating complex technical conversations and building strong relationships.
• A strong public profile (blogs, GitHub, conference talks) demonstrating expertise and passion.

Compensation & Benefits

• The base salary will be determined by location, experience, and internal pay equity. Base salary ranges provided:
  • Level 4: 184,000 USD - 287,500 USD
  • Level 5: 224,000 USD - 356,500 USD
• Eligibility for equity and company benefits (link to benefits provided by NVIDIA).

Additional Information

• Applications for this job will be accepted at least until September 20, 2025.
• NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.