Senior Applied Research Scientist – Core AI & Document Intelligence

What You’ll Do

Research & Model Development

• 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.

Applied AI & Product Impact

• Build and ship 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.

Qualifications

Technical Expertise

• 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.

Optional (but Highly Valued)

• 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.

What Sets You Apart

• 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.

Benefits

• - Ability to save in 401(k) plans
• - Comprehensive Healthcare and Dental Benefits

Why Tensorlake?

We’re building something foundational for how companies integrate AI into knowledge workflows, RAG pipelines, document agents, and real-world enterprise applications. If you’re excited about shaping AI products that matter, and you enjoy bridging research with engineering execution, this is the role to join. LinkedIn