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Member of Technical Staff – Applied Research

LlamaIndex

AI Research Engineer focusing on vision-language models for document processing in a fast-growing AI startup with strong open-source initiatives.

Posted 7/8/2026full-timeSan Francisco • California • 🇺🇸 United StatesLead💰 $180,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and training vision-language models, with a strong foundation in machine learning and proficiency in Python and PyTorch. Capable of building data pipelines and evaluating model performance to enhance document processing and understanding.

Highest-signal resume keywords

Machine Learning EngineeringPython ProgrammingPyTorch FrameworkComputer VisionDocument AI

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel TrainingBenchmarkingData CurationSynthetic Data GenerationOCRModel EvaluationPerformance ImprovementDocument ProcessingTechnical Writing

Soft Skills

AdaptabilitySelf-DirectionCommunicationEngineering Judgment

Tools & Technologies

Modern ML ToolingAI Coding Workflows

Industry Keywords

Vision-Language ModelsNLPAgentic AI SystemsExtractionStartup Experience

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Develop and train vision-language models for document processing and document understanding.
Build data pipelines for data curation, synthetic data generation, labeling, and benchmark creation.
Evaluate base models and perform post-training or fine-tuning to hit specific performance targets.
Improve model accuracy, latency, and cost-effectiveness across real-world document workflows.
Design and maintain benchmarks to measure extraction quality, layout understanding, OCR performance, reasoning accuracy, and end-to-end system reliability.
Work with messy real-world documents, including PDFs, scanned documents, tables, charts, forms, and multi-page enterprise documents.
Collaborate with engineering to move successful research prototypes into production.
Work directly with customers when needed to translate product requirements into benchmarks, experiments, and model improvements.
Stay close to the latest research in vision-language models, document AI, post-training, synthetic data, and agentic systems.
Use modern AI coding workflows and tools to move quickly.

Requirements

What you’ll need

3–7 years of experience in machine learning engineering, applied research, or research engineering.
Strong ML foundation, including hands-on experience benchmarking and training models.
Strong Python skills and comfort with modern ML tooling, especially PyTorch.
Experience with computer vision, vision-language models, NLP, document AI, OCR, extraction, or agentic AI systems.
Ability to build experiments, evaluate results, and iterate quickly toward measurable performance improvements.
Strong engineering judgment and ability to write clean, production-quality code.
Comfort working in a fast-paced startup environment with high ownership and limited structure.
Adaptable, scrappy, and self-directed — someone who can figure things out without waiting to be told.
Strong technical writing and communication skills.
Prior startup experience, especially at an early-stage or high-growth AI company is a nice to have.

Benefits

Comp & perks

Work on a core AI infrastructure problem: making complex documents understandable and actionable for AI systems.
Build production systems at the frontier of vision-language models and document AI.
Join a fast-growing startup with strong open-source adoption and commercial traction.
Work directly with technical founders and a highly ambitious engineering team.
Have real ownership over model quality, product capability, and technical direction.

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Member of Technical Staff – Applied Research

Core Competencies

ATS Keywords

Tech Stack

About the role

Requirements

Benefits

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