Responsibilities

• Architect, build, and ship end-to-end solutions for Media use cases—spanning multi-agent coordination, long-horizon reasoning, planning, and tool use—along with high-performance RAG pipelines over heterogeneous media assets (text, code, images, audio, video) to tackle real production challenges such as content generation, localization, metadata enrichment, personalization, recommendation, and ad operations.
• Act as a hands-on technical advisor and main domain expert during the pre- and post-sale stages. Work closely with customer AI researchers, engineers, and developers to build, prototype, and deploy solutions on NVIDIA platforms.
• Optimize performance and total cost of ownership using the full NVIDIA AI and media stack—and build hands-on proofs-of-concept, reference architectures, and reusable blueprints that serve as production templates and accelerate time-to-value. Post-training open sourced models to meet the requirements.
• Partner with NVIDIA engineering, product, and sales teams to secure build wins, translate customer feedback into actionable product and roadmap insights, and scale global expertise through technical collateral, workshops, and developer communities.

Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience) and 8+ years in broadcast and/or telco CDN industry.
• Expertise in engineering of transitions from SDI to IP, media over IP technologies such as SMPTE 2110, SRT, and RIST.
• Understanding of traditional and new broadcast control technologies (such as NMOS, LAWO VSM).
• Proven knowledge of audio and video formats and codecs
• Hands-on experience with CUDA, Python, or C++.
• Familiarity working with AI models for audio and video enhancement. Hands-on experience deploying containerized AI/ML, GPU-accelerated, distributed workloads.
• Experience with at least one public cloud; AWS experience with EKS, SageMaker, EC2 GPU instances, lambda, VPC, IAM, S3, load balancing and proxies (NLB), cloudwatch logs, streaming data (Kinesis).
• Solid understanding of Ansible and/or Terraform and IP based networking, specifically multicast capabilities and its application in media and telco networks.
• Production Kubernetes experience, including deployments, services, ingress, storage, networking, RBAC, secrets, resource management, autoscaling, and troubleshooting. knowledge of Docker, Helm, kubectl, Git, CI/CD, and shell scripting.
• Exposure to REST APIs, gRPC, Streaming APIs.

Preferred

• Working experience in timing technologies (PTP).
• Knowledge of NVIDIA SDKs and accelerated computing for vision (Rivermax, Deepstream, NVENC, NVDEC).
• Expertise in deployment of AI models or tools within media and video streaming workflows in production.
• Cloud certificates such as AWS Certified Solutions Architect – Associate or higher or Microsoft Certified: Azure Solutions Architect Expert or Google Cloud Professional Cloud Architect
• Certified Kubernetes Application Developer (CKAD)