Jobs
Benefits & Perks
•Top Tier compensation with equity
•Health, dental, and vision coverage
•Flexible PTO policy
•Learning and development stipend
•Remote work flexibility
Required Skills
SQL
Python
Airflow
Join us and help shape the future of AI by defining the narrative around document understanding.
ABOUT THE ROLE:
We are seeking exceptional AI engineers to join our core document understanding team. You will work at the intersection of computer vision, natural language processing, and production ML systems to push the boundaries of what's possible in document parsing and understanding.
Our document understanding team builds the intelligence behind Llama Parse, Llama Extract, and our other processing products. These systems are processing millions of complex documents including PDFs, PowerPoints, Word documents, and spreadsheets. Your work will directly impact thousands of developers building RAG applications and document agents, while also contributing to our open-source frameworks that shape how the industry approaches document processing.
Depending on your background and interests, you might focus more on data curation and evaluation, model fine-tuning and experimentation, or ML infrastructure and production systems. We're hiring multiple people and will work with you to find the best fit.
RESPONSIBILITIES:
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Develop, train, and optimize machine learning models for document structure understanding, table extraction, layout analysis, and multimodal content processing
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Build robust data pipelines, evaluation frameworks, and experimentation infrastructure
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Design and implement production ML systems that handle complex, real-world documents at scale
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Stay current with latest advances in vision-language models, document AI, and multimodal learning
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Collaborate with engineering teams to integrate ML innovations into production APIs
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Contribute to both our open-source frameworks and enterprise offerings
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Drive technical decisions while balancing research exploration with product delivery
REQUIRED QUALIFICATIONS:
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3-7 years of experience in machine learning engineering or applied research
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Strong software engineering fundamentals with production Python experience (modern tooling: uv, ruff, mypy, Pydantic)
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Hands-on experience training, fine-tuning, or deploying ML models in production
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Deep understanding of modern ML techniques, particularly in computer vision, NLP, or multimodal learning
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Experience with at least one of: data pipeline development, model training/fine-tuning, or ML infrastructure
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Ability to read and implement from research papers and technical specifications
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Track record of executing with high intensity in fast-paced environments
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Strong technical communication skills and comfort with open-source collaboration
PREFERRED QUALIFICATIONS:
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Experience with vision-language models, transformer architectures, or model fine-tuning (LoRA, QLoRA)
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Experience building evaluation frameworks, benchmarks, or data quality pipelines
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Experience with model serving frameworks (vLLM, TensorRT, ONNX) or MLOps tools
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Experience specifically with document understanding, OCR, or layout analysis
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Contributions to open-source ML projects or frameworks
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Experience with LLM applications and RAG systems
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Strong understanding of model optimization techniques (quantization, distillation, pruning)
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Experience with Docker/Kubernetes and distributed systems
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Active participation in ML research community
LOCATION:
We offer a hybrid-friendly culture based out of our downtown San Francisco office. Remote candidates will be considered for exceptional fits.
WHY JOIN US?
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Impactful Mission: Work on innovative AI products that redefine how knowledge is accessed and utilized. Your models will process millions of documents and directly impact thousands of developers.
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Cutting-Edge Technology: Work with the latest vision-language models, contribute to open-source frameworks used industry-wide, and shape the future of document AI.
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Collaborative Team: Join a focused team of passionate engineers and researchers committed to pushing the boundaries of what's possible in document understanding.
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Technical Autonomy: Significant creative freedom to explore new approaches while maintaining focus on delivering high-quality, production-ready solutions.
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Growth Opportunities: Be at the forefront of the AI revolution, with ample opportunities to grow alongside our scaling organization. Shape your role based on your interests and strengths.
ADDITIONAL BENEFITS:
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Competitive base salary and equity compensation
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Comprehensive medical/dental/vision coverage for you and your family
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Unlimited paid time off policy
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Daily catered lunch and snacks in the San Francisco office
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Budget for conferences, research materials, and professional development
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Access to cutting-edge compute resources and research tools
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Llama Index does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, employees, or any other organization location. Llama Index is not responsible for any fees related to unsolicited resumes.
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About LlamaIndex

LlamaIndex
Series ALlamaIndex is an open-source data framework that enables developers to connect custom data sources to large language models. The company provides tools and infrastructure for building LLM-powered applications with retrieval-augmented generation capabilities.
1-50
Employees
San Francisco
Headquarters
Reviews
4.1
44 reviews
Work Life Balance
3.8
Compensation
4.2
Culture
4.4
Career
4.3
Management
3.6
82%
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Pros
Cutting-edge technology stack and interesting technical challenges
Competitive compensation packages with equity
Strong engineering culture with focus on code quality
Cons
Work-life balance can be challenging during product launches
Internal politics in some teams
Organizational changes and restructuring can be disruptive
Salary Ranges
4 data points
Senior/L5
Staff/L6
Senior/L5 · Full Stack Product Engineer
2 reports
$260,000
total / year
Base
$200,000
Stock
-
Bonus
-
$260,000
$260,000
Interview Experience
1 interviews
Difficulty
4.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 0%
Negative 100%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
System Design Interview
5
Team Matching
6
Offer
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
FAISS/Vector Database
LLM/AI Experience
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