Senior AI Scientist: Document Intelligence & Multimodal

Tensorlake Inc; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

401(k) plan

Healthcare coverage

Job summary

Tensorlake Inc in San Francisco is seeking an experienced AI/ML researcher to lead design and experimentation on state-of-the-art models for document understanding and multimodal reasoning. You will evaluate vision-language models, RAG frameworks, and grounding techniques to drive product impact, and develop benchmarks and evaluation methods for real-world tasks.

You will build production-ready AI components (table extraction, structure parsing, semantic indexing) and collaborate with

Qualifications

• 5+ years experience in AI/ML research and applied systems.
• Deep background in document understanding, multimodal AI, NLP + CV integration.
• Hands-on experience with vision-language models, RAG frameworks, and context-aware retrieval.

Responsibilities

• Lead design and experimentation on state-of-the-art models for document understanding, multimodal reasoning, and deep content extraction.
• Research, evaluate, and integrate latest vision-language models and retrieval/ grounding techniques to drive product impact.
• Develop benchmarks, datasets, and evaluation methodologies for real-world document AI tasks.
• Build and ship production-ready AI components and deploy models at scale, from prototype to platform features.
• Collaborate with customers and partners to validate use cases, including LLM orchestration and agent integration.

Skills

AI/ML research

Multimodal AI

NLP + CV integration

Product delivery

Tools

PyTorch

Python

LoRA

Quantization

RAG frameworks

Embedding-based systems

Job description

Tensorlake Inc in San Francisco is seeking an experienced AI/ML researcher to lead design and experimentation on state-of-the-art models for document understanding and multimodal reasoning. You will evaluate vision-language models, RAG frameworks, and grounding techniques to drive product impact, and develop benchmarks and evaluation methods for real-world tasks.

You will build production-ready AI components (table extraction, structure parsing, semantic indexing) and collaborate with