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# Applied Research Scientist - Core AI & Document Intelligence

- **Company:** Tensorlake, Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Frameworks, Computer Vision, Automated Storage and Retrieval Systems, Encodings, Python (Programming Language), Machine Learning, Language Modeling, Enterprise Software Applications, Pytorch, Large Language Models, Deep Learning
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-applied-research-scientist-core-ai-document-intelligence-current-8-8291627

## About the Role

* 5+ years experience in AI/ML research and applied systems; strong record of delivering results.
 * 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.

Applied AI & Engineering

 * 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., * Experience with open-source frameworks and community contributions
 * Background in agents, RAG architectures, retrieval systems, and context engineering.
 * Experience designing benchmarks, quality metrics, or curated datasets for complex tasks.

## Description

* 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., * 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., * You balance deep technical curiosity with product focus and can speak fluently to both ML research and engineering issues.
 * You've shipped models and systems that are used by developers or customers in real scenarios (not just research demos).
 * You are comfortable working in a fast-moving startup environment where priorities evolve and innovation is part of the culture.


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