Solution Architect, Computer Vision – Media and Entertainment

Reposted 4 Days Ago
Be an Early Applicant
4 Locations
In-Office or Remote
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Solutions Architect will drive NVIDIA technology adoption in the Media and Entertainment sector, focusing on AI platforms, solution architecture, and customer engagement for video analytics, content generation, and scalable solutions.
Summary Generated by Built In

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 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.

What We Need to See:

  • 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.

Ways to Stand Out from the Crowd:

  • 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.

  • Strong background in containerization (Docker/K8s) and optimizing distributed inference for Large Vision Models.

We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you.

Skills Required

  • MS or PhD in Computer Science, Computer Vision, Engineering, or related field (or equivalent experience)
  • 5+ years of experience in Computer Vision
  • Hands-on experience with Vision Language Models and/or Generative AI models
  • Proficiency with ML frameworks like PyTorch
  • Experience managing AI workloads across Edge and Cloud environments

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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