Lead research and product development of document understanding and multimodal AI. Design and evaluate VLMs, RAG and retrieval systems; build benchmarks and datasets; ship production-ready components (table extraction, structure parsing, semantic indexing, multimodal QA); and work with engineering, product, and customers to deploy models and agentic workflows at scale.
About Tensorlake Inc
Tensorlake is a serverless platform for agentic applications and Document Ingestion. It provides foundational infrastructure such as serverless compute, code sandboxes, durable execution and unstructured data ingestion APIs to developers in enterprises. We aim to push the frontier of AI that understands real, complex documents and detailed workflows — not just text extraction, but contextual reasoning and scalable application systems.
This role is for an experienced scientist who thrives both in innovating foundational models and building usable, robust AI systems for real users.
- 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 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.
- 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.
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
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
Similar Jobs
Healthtech • Social Impact • Software
Own and build Grow Therapy's data security infrastructure: automated data classification, field-level masking/tokenization, encryption and key management, secure data connectors to AI tooling, and access controls. Define a multi-year vision, implement pipelines and services, and partner across Data, Engineering, and Detection & Response to make secure-by-default the company standard.
Productivity • Software • App development • Automation
Lead and scale a Quality Assurance team that validates and qualifies open-source leads for sales readiness. Own hiring, training, QA standards, KPI tracking, and process improvements while partnering with SDRs, Sales, and partners to drive pipeline impact.
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Manage and grow a portfolio of strategic fleet accounts across MN, ND, and SD. Drive retention, expansion, and new business (70% account management / 30% new business), negotiate deals, coordinate cross-functional delivery, maintain CRM and pipeline, provide forecasts, and travel frequently to support customer engagement and solution implementation.
Top Skills:
Crm SystemsExcelMicrosoft PowerpointMicrosoft Word
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
