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.
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.
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/
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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.Skills Required
- Master's or PhD in Computer Science, Engineering, or equivalent experience
- 7+ years of experience in applied AI/ML
- Hands-on experience with document understanding and visual content analysis
- Proven experience building or optimizing vision-language models and Omni models
- Familiarity with NVIDIA's ecosystem, including TensorRT-LLM, NeMo, RAPIDS, or equivalent training and inference frameworks
- Excellent communication skills with research scientists, ML engineers, and business collaborators
- Experience building multimodal systems involving audio, video, 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 using quantization, pruning, or architectural changes
- Published work or open-source contributions in multimodal learning
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.
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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.
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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.
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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.
NVIDIA Insights
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.”
