Role Overview
Our team is looking for a Senior Solutions Architect with hands-on experience training and optimizing multimodal AI solutions for image and video document intelligence. In this role, you will serve as the technical expert for EMEA AI Natives companies building Multimodal applications for content analysis and recommendations. Using NVIDIA software and Hardware stack, you will help customers tackle their most complex AI challenges, from building document intelligence pipelines to scaling text/image/video understanding applications for production. Working alongside NVIDIA research, engineering and product teams, you will translate modern AI technologies into accurate, production-ready solutions that deliver measurable business value.
What You'll be Doing:
- Develop technical relationships with customers building multimodal AI systems for document intelligence, personalization, and image/video analysis, assisting them from architectural planning through to deployment in production.
- Guide customers on model training strategies across modalities: layout-aware document encoders, user-item interaction models, and spatiotemporal video representations.
- Tackle Vision content challenges: image resolutions, vision encoder optimization for production latency constraints, efficient video frame sampling, temporal reasoning.
- Represent customer needs directly to NVIDIA's product teams, translating field insights into roadmap decisions across NeMo, TensorRT-LLM, Dynamo and RAPIDS.
- Engage the developer community through hackathons, technical talks, demos, and reference blueprints.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer www.nvidiabenefits.com/. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN.
What We Need to See:
- MS or PhD in Computer Science, Engineering, or equivalent experience will be considered.
- 7+ years in applied AI/ML, having hands-on experience on document understanding, visual content analysis.
- Proven track record in 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.
Ways to Stand Out from the Crowd:
- You have built multimodal AI systems that handle multiple modalities (audio, video) and complex structures: layouts, tables, and multi-page reasoning.
- Understanding of retrieval and search systems: dense retrieval, ANN indexing, re-ranking pipelines.
- You have optimized vision encoders for production: quantization, pruning, or architectural changes to hit real latency budgets.
- You have published work or open-source contributions in multimodal learning.
