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Solution Architect, Computer Vision – Media and Entertainment
NVIDIASolutions Architect specializing in Computer Vision and Generative AI for NVIDIA's EMEA Media & Entertainment Team. Driving technology adoption and building AI platforms for key M&E customers.
Tech Stack
Tools & technologiesCloudPyTorch
About the role
Key responsibilities & impact- Work on our EMEA M&E Solution Architects Team to drive NVIDIA technology adoption at key M&E customers.
- Secure builds in Data Center, Edge, and Cloud Deployments.
- Become a trusted technical advisor for our EMEA-based customers, helping them architect end-to-end agentic pipelines like video analytics, archive analysis, and automated metadata extraction, etc.…
- Lead customer proof-of-concepts (PoCs) using next-generation AI platforms to solve complex M&E use cases, including automated video summarization, agentic and Generative AI workflows for image and video synthesis.
- Design and implement scalable inference solutions that manage the transition from Edge-based processing to massive Cloud clusters, addressing the unique throughput and latency challenges of VLMs and Diffusion models.
- Partner with NVIDIA Engineering, Product, and Sales teams to optimize AI techniques bridging algorithms and systems, providing critical field feedback to influence NVIDIA’s future M&E software and hardware roadmaps.
- Drive adoption of NVIDIA’s Accelerated Compute Platforms, focusing on growing our customers’ capabilities in deploying modern AI architectures, from traditional CNNs to transformer-based generative models.
Requirements
What you’ll need- MS or PhD in Computer Science, Computer Vision, Engineering, or related technical field (or equivalent experience)
- 5+ years of experience in Computer Vision, with a strong foundation in traditional Detection, Segmentation, and Tracking algorithms.
- Hands-on experience developing or implementing Vision Language Models (VLMs) and/or Generative AI models applied to visual and video content creation (e.g., Stable Diffusion, GANs, or Transformer-based synthesis).
- Proficiency with ML frameworks like PyTorch and a deep understanding of the challenges involved in model deployment, customization, quantization and inference at scale.
- Experience managing AI workloads across diverse environments, from resource-constrained Edge devices to high-performance Cloud infrastructure.
- Excellent presentation skills with the ability to bridge the gap between deep technical discussions with engineers and value-based conversations with executives.
Benefits
Comp & perks- Competitive salary
- Flexible working hours
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Computer VisionDetection algorithmsSegmentation algorithmsTracking algorithmsVision Language Models (VLMs)Generative AI modelsPyTorchmodel deploymentquantizationinference at scale
Soft Skills
presentation skillstechnical advisorycommunicationcollaborationproblem-solving
Certifications
MS in Computer SciencePhD in Computer ScienceEngineering degree