Lead AI Scientist - Document Intelligence & Production

Aimlroles; San Francisco (CA); Sur place; USD 180 000 - 280 000; Plein temps

Avantages offerts par ce poste

401(k)

Healthcare

Dental

Résumé du poste

Tensorlake Inc. is seeking an experienced scientist to lead design and experimentation on state-of-the-art models for document understanding and multimodal AI, driving product impact with robust, scalable AI systems.

You will research vision-language models, retrieval frameworks, RAG, and grounding techniques, and build production-ready components such as table extraction, structure parsing, and semantic indexing. The role blends research with engineering execution in a fast-moving startup.

Qualifications

• 5+ years experience in AI/ML research and applied systems.
• Deep background in document understanding, multimodal AI, NLP + computer vision integration.
• Hands-on experience with vision-language models, RAG frameworks, context-aware retrieval, agentic AI, and embedding-based systems.
• Track record of “research → product” delivery: turning prototypes into robust pipelines, APIs, or services.
• Experience optimizing and fine-tuning large models, knowledge of quantization/LoRA/efficient training.
• Proficiency with deep learning frameworks (PyTorch preferred), Python, and scalable ML tooling.

Responsabilités

• Lead design and experimentation on state-of-the-art models for document understanding, multimodal reasoning, and deep content extraction.
• Research, evaluate, and integrate the latest vision-language models (VLMs), retrieval frameworks, RAG systems, and grounding techniques to drive product impact.
• Develop new benchmarks, datasets, and evaluation methodologies tailored to real-world document AI tasks.
• Build production-ready AI components (e.g., table extraction, structure parsing, semantic indexing, multimodal QA, agentic workflows).
• Work with engineering and product partners to deploy models at scale — from prototype to integrated platform features.
• Collaborate closely with customers and partners to prioritize and validate use cases, including LLM orchestration, context engineering, and agent integration.

Connaissances

AI/ML research

Document understanding

Multimodal AI

NLP + computer vision

Vision-language models

RAG frameworks

Context-aware retrieval

Agentic AI

Embedding-based systems

PyTorch

Python

Scalable ML tooling

Outils

PyTorch

Python

Description du poste

Tensorlake Inc. is seeking an experienced scientist to lead design and experimentation on state-of-the-art models for document understanding and multimodal AI, driving product impact with robust, scalable AI systems.

You will research vision-language models, retrieval frameworks, RAG, and grounding techniques, and build production-ready components such as table extraction, structure parsing, and semantic indexing. The role blends research with engineering execution in a fast-moving startup.