Senior Solutions Architect – Multimodal AI
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Job Description
Senior Solutions Architect guiding EMEA AI companies in building production-ready multimodal document, image, and video intelligence solutions with NVIDIA technology.
Responsibilities:
- Develop technical relationships with customers building multimodal AI systems for document intelligence, personalization, and image/video analysis, from architectural planning through production deployment.
- Guide customers on model training strategies across modalities, including layout-aware document encoders, user-item interaction models, and spatiotemporal video representations.
- Address vision content challenges such as image resolutions, vision encoder optimization for production latency constraints, efficient video frame sampling, and temporal reasoning.
- Represent customer needs to NVIDIA product teams and translate field insights into roadmap decisions across NeMo, TensorRT-LLM, Dynamo, and RAPIDS.
- Engage the developer community through hackathons, technical talks, demos, and reference blueprints.
- Translate modern AI technologies into accurate, production-ready solutions delivering measurable business value.
Requirements:
- MS or PhD in Computer Science, Engineering, or equivalent experience will be considered.
- 7+ years in applied AI/ML.
- Hands-on experience with document understanding and visual content analysis.
- Proven track record building or optimizing VLMs and Omni models.
- Familiarity with NVIDIA's ecosystem: TensorRT-LLM, NeMo, RAPIDS, or equivalent training and inference frameworks.
- Excellent communication skills; comfortable with research scientists, ML engineers, and business collaborators.
- Experience with multimodal AI systems handling multiple modalities, including audio and video, and complex structures such as layouts, tables, and multi-page reasoning.
- Understanding of retrieval and search systems, including dense retrieval, ANN indexing, and re-ranking pipelines.
- Experience optimizing vision encoders for production using quantization, pruning, or architectural changes.
- Published work or open-source contributions in multimodal learning.
Benefits:
- Highly competitive salaries
- Comprehensive benefits package
- Equal opportunity employment
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