Senior Solutions Architect – Multimodal AI

NVIDIA

Senior Solutions Architect guiding EMEA AI companies in building production-ready multimodal document, image, and video intelligence solutions with NVIDIA technology.

Posted 9/8/2026full-timeRemote • 🇵🇱 PolandSenior💰 PLN 292,500 - PLN 507,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing multimodal AI systems, optimizing vision encoders, and translating customer needs into actionable insights. Proficient in guiding model training strategies and engaging with diverse stakeholders to deliver production-ready AI solutions.

Highest-signal resume keywords

7+ Years In Applied AI/MLHands-On Experience With Document UnderstandingFamiliarity With NVIDIA's EcosystemExperience Optimizing Vision EncodersPublished Work In Multimodal Learning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model Training StrategiesDocument EncodersVisual Content AnalysisVLMs And Omni ModelsRetrieval And Search SystemsDense RetrievalANN IndexingQuantizationPruningArchitectural Changes

Soft Skills

Excellent Communication Skills

Tools & Technologies

TensorRT-LLMNeMoRAPIDS

Certifications & Qualifications

MS Or PhD In Computer ScienceEngineering

Industry Keywords

Multimodal AI SystemsImage/Video AnalysisProduction DeploymentTemporal ReasoningLayout-Aware Document Encoders

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Equal opportunity employment