NVIDIA
Media and Entertainment
SolutionArchitect,ComputerVision
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“Solution Architect, Computer Vision at NVIDIA. Skills: Computer Vision, Generative AI, AI platforms, inference solutions. Drive NVIDIA technology adoption. Secure builds in Data Center”
What You'll Achieve.
drive measurable impact across global media ecosystems; growing our customers’ capabilities
Industry & Context.
navigate the challenges of deploying state-of-the-art models at scale; addressing the unique throughput and latency challenges
What They're Looking For.
Must Have
5+ years of experience in Computer Vision, Hands-on experience developing or implementing Vision Language Models (VLMs) and/or Generative AI models applied to visual and video content creation, Proficiency with ML frameworks like PyTorch, deep understanding of the challenges involved in model deployment, customization, quantization and inference at scale, Experience managing AI workloads across diverse environments, Excellent presentation skills
Nice to Have
Expertise with NVIDIA-specific SDKs such as DeepStream, TensorRT, Triton Inference Server, TAO, and the Holoscan or NeMo frameworks, Experience with 3D rendering, lighting or familiarity with scene creation tools like NVIDIA Omniverse, background in containerization (Docker/K8s), optimizing distributed inference for Large Vision Models
What You'll Do.
Drive NVIDIA technology adoption
Secure builds in Data Center
Secure builds in Edge
Secure builds in Cloud Deployments
Architect end-to-end agentic pipelines
Lead customer proof-of-concepts
Solve complex M&E use cases
Design and implement scalable inference solutions
Manage the transition from Edge
Manage transition to massive Cloud clusters
Optimize AI techniques
Influence NVIDIA’s future roadmaps
Drive adoption of Accelerated Compute Platforms
Deploy modern AI architectures
How You'll Work.
Team & Collaboration
Partner with NVIDIA Engineering; Partner with NVIDIA Product; Partner with NVIDIA Sales teams
Communication Scope
presentation skills; bridge the gap between deep technical discussions; value-based conversations with executives
Full Job Description
Are you passionate about redefining how the world creates, consumes, and analyzes video content? We are looking for a Solutions Architect to join NVIDIA’s EMEA Media & Entertainment (M&E) Team, focusing on the intersection of traditional Computer Vision and the frontier of Generative AI. In this role, you will help leading ISVs and M&E organizations build AI platforms that bring intelligence to every frame—from real-time video analytics and automated summarization to AI-driven marketing content generation that blends 2D and 3D assets. You will combine your deep expertise in detection, tracking, and content generation powered by AI with NVIDIA’s top GPU and AI platforms. This role aims to drive measurable impact across global media ecosystems. We need a creative, hands-on individual to help our partners navigate the challenges of deploying state-of-the-art models at scale, whether on Edge devices for real-time analysis or across Large Cloud deployments for massive content management. **What you will be doing:** * You will work on our EMEA M&E Solution Architects Team to drive NVIDIA technology adoption at key M&E customers. You will 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 i
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