Multimodal AI Engineer, Document Understanding Job at LlamaIndex (San Francisco)

Senior AI Engineer

This role will be tasked with applying machine learning/deep learning to the aut...

Location

United States , Belmont

Salary:

170000.00 - 210000.00 USD / Year

Volkswagen AG

Expiration Date

Until further notice

Requirements

6-8 years of professional experience post graduate degree preferred
4+ years' Deep Learning experience post graduate degree preferred
Master's Degree in Computer Science or equivalent
PhD Strongly Preferred
Strong knowledge of different machine learning algorithms
Proficiency in deep learning techniques and frameworks
Strong understanding of traditional machine learning algorithms and their applications
Expertise in computer vision, including object detection, image segmentation, and image recognition
Proficiency in NLP techniques, including sentiment analysis, text generation, and language understanding models
Experience with multimodal language modeling and applications

Job Responsibility

Applying machine learning/deep learning to the automotive industry
Maintaining and enhancing existing machine learning modules for autonomous vehicles
Designing and implementing new machine learning based approaches based on existing frameworks
Keeping up to speed with the state of the art of academic research and technology in the industry
Coordinating with engineers at the ICC and in Germany on the development of autonomous driving software
Transferring technologies and solutions to Volkswagen Group development divisions
Developing technical specifications and documentation
Representing Volkswagen Group in the technical community, such as at conferences

Fulltime

AI Content Engineer

Join us and help shape the future of AI by architecting next-generation knowledg...

Location

United States , San Francisco

Salary:

Not provided

LlamaIndex

Expiration Date

Until further notice

Requirements

Experience in software engineering (ML engineering + research a bonus)
Strong software engineering fundamentals with production Python experience
Understanding of modern ML techniques, particularly in computer vision, NLP, or multimodal learning
Demonstrated ability to write clearly, quickly, and authentically about technical topics
Bias toward shipping - comfortable publishing at blog pace, not paper pace
Ability to read, understand, and synthesize research papers rapidly
Scrappy and self-directed - can identify what's worth writing about and execute end-to-end
Track record of high-velocity output in fast-paced environments

Job Responsibility

Design, build, and maintain comprehensive benchmarks for document parsing and understanding
Publish high-quality technical content at a weekly cadence (blog posts, benchmark reports, technical comparisons, tutorials)
Stay deeply current with the document AI landscape - new models, papers, competitors, techniques
Run experiments and translate findings into publishable artifacts quickly
Produce technical analyses that demonstrate our capabilities against alternatives
Contribute to open-source examples, notebooks, and documentation
Collaborate with the core ML team to surface improvements and capabilities worth highlighting
Engage authentically with the developer community through technical content (not conferences/events)

What we offer

Shape the Narrative: Your content will define how developers think about document understanding. You'll have direct influence on market perception
Technical Credibility: Work with cutting-edge document AI systems processing millions of documents. Your benchmarks and analyses will be grounded in real capabilities
High Autonomy: Significant freedom to identify what matters and publish quickly. No lengthy approval chains
Growth Opportunity: Help build this function from the ground up as we scale

Fulltime

AI Solutions Architect

We are looking for a highly skilled AI Architect with deep expertise in Generati...

Location

India , Hyderabad

Salary:

Not provided

NStarX

Expiration Date

Until further notice

Requirements

Minimum 10 years of experience in ML/AI solution architecture
Deep expertise in Generative AI: LLMs, Vision/Video models, Digital Avatars, RAG systems, and multimodal architectures
Strong experience in ML engineering, data pipelines, and scalable model APIs
Hands-on experience with Nvidia GPU systems, CUDA stack, TensorRT, vLLM/Ollama, and model optimization
Experience building AI on edge devices (Intel, AMD, Qualcomm NPUs, AI PCs)
Proficiency in AWS and Azure cloud ecosystems, including GPU-based deployments
Strong knowledge of Python, ML frameworks (PyTorch, TensorFlow), model serving frameworks, and MLOps tools
Proven track record of architecting POC, MVP, and production-grade AI products
Strong architectural documentation and diagramming skills (Mermaid, Draw.io, Lucidchart, ArchiMate)
Excellent communication skills for client presentations and internal leadership discussions

Job Responsibility

Design and architect LLM-based systems using both open-source (Llama, Mistral, etc.) and proprietary (OpenAI, Azure OpenAI, Anthropic, etc.) models
Architect video-based AI systems, including Digital Human Avatars, Video Generation, Video-to-Text, and multimodal pipelines
Build end-to-end GenAI pipelines including data ingestion, preprocessing, retrieval, fine-tuning (LoRA, QLoRA, DAPT), evaluation, guardrailing, and deployment
Define and orchestrate data pipelines, ML workflows, vector search architecture, and embedding strategies
Build scalable, secure ML engineering wrappers around models (inference servers, orchestration layers, API microservices)
Oversee experimentation frameworks, evaluation methodologies, and MLOps integration
Architect AI solutions on AWS and Azure (preferred), including GPU clusters, model hosting, DevOps/MLOps, and autoscaling
Work with Nvidia GPU server stacks (DGX, H200, H100, L40S) and edge AI systems (Intel, AMD, Qualcomm AI PCs)
Optimize AI workloads across heterogeneous compute environments
Lead AI architecture across POC → MVP → GA → production-scale phases

What we offer

Competitive base + commission
Fast growth into leadership roles

Fulltime

Data Engineer (AI / ML)

We are investing massively in developing next-generation AI tools for multimodal...

Location

United Kingdom; Greece , London

Salary:

Not provided

Satalia

Expiration Date

Until further notice

Requirements

High proficiency in Python and SQL
Strong knowledge of data structures, data modelling, and database operation
Proven hands-on experience building and deploying data solutions on a major cloud platform (AWS, GCP, or Azure)
Familiarity with containerization technologies such as Docker and Kubernetes
Familiarity with Retrieval-Augmented Generation (RAG) applications and modern AI/LLM frameworks (e.g., LangChain, Haystack, Google GenAI, etc.)
Demonstrable experience designing, implementing, and optimizing robust data pipelines for performance, reliability, and cost-effectiveness in a cloud-native environment
Experience in supporting data science workloads and working with both structured and unstructured data
Experience working with both relational (e.g., PostgreSQL, MySQL) and NoSQL databases
Experience with a big data processing framework (e.g., Spark)

Job Responsibility

Collaborate closely with data scientists, architects, and other stakeholders to understand and break down business requirements
Collaborate on schema design, data contracts, and architecture decisions, ensuring alignment with AI/ML needs
Provide data engineering support for AI model development and deployment, ensuring data scientists have access to the data they need in the format they need it
Leverage cloud-native tools (GCP/AWS/Azure) for orchestrating data pipelines, AI inference workloads, and scalable data services
Develop and maintain APIs for data services and serving model predictions
Support the development, evaluation and productionisation of agentic systems with: LLM-powered features and prompt engineering
Retrieval-Augmented Generation (RAG) pipelines
Multimodal vector embeddings and vector stores
Agent development frameworks: ADK, LangGraph, Autogen
Model Context Protocol (MCP) for integrating agents with tools, data and AI services

What we offer

enhanced pension
life assurance
income protection
private healthcare
Remote working
Truly flexible working hours
Generous Leave - 27 days holiday plus bank holidays and enhanced family leave
Annual bonus
Impactful projects
People oriented culture

Fulltime

Principal ML Engineer, CoreAI

You’ll help build core generative AI and multimodal capabilities that power cust...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field and 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, Python or equivalent experience
Advanced degree in Computer Science, Machine Learning, or related field
Demonstrated technical leadership through influence (e.g., leading designs, setting architecture direction, mentoring engineers)
Experience with prompt engineering, retrieval-augmented generation (RAG), and memory/agent frameworks
Experience building and shipping generative AI systems (including multimodal scenarios)
Familiarity with compliance and security standards in enterprise AI solutions
Track record of delivering enterprise-facing AI products at scale
Experience building and operating ML/AI systems in cloud environments
familiarity with MLOps practices (Azure a plus)
Experience partnering with cross-functional stakeholders to define requirements and drive technical decisions

Job Responsibility

Design, build, and operate production-grade generative AI and multimodal systems, with end-to-end ownership from concept through deployment and service operations
Lead technical design for core GenAI capabilities (e.g., retrieval-augmented generation, context and memory, orchestration) and make data-driven tradeoffs across quality, latency, cost, and safety
Define and improve model and system quality using evaluation frameworks, experiment design, and production telemetry
ensure robust testing and regression coverage
Collaborate with security, privacy, and compliance partners to build solutions that meet enterprise requirements and align with Responsible AI standards and practices
Provide technical leadership across teams by setting direction, reviewing designs, unblocking execution, and mentoring engineers on architecture, coding standards, and ML engineering best practices
Partner with product and customers to understand scenarios, translate requirements into well-designed APIs and developer experiences, and drive adoption through documentation and samples

Fulltime

AI Engineer

Our client is building a next-generation video platform that leverages artificia...

Location

Brazil

Salary:

52.00 USD / Hour

G2i Inc.

Expiration Date

Until further notice

Requirements

Proven experience training AI models (this is mandatory — not limited to API integration or fine-tuning)
Strong background in machine learning frameworks such as PyTorch or TensorFlow
Experience with computer vision, video analysis, or multimodal AI is a strong plus
Familiarity with Python and standard ML toolkits
Ability to work independently and deliver results in a short time frame
Based in Brazil and available for part-time engagement (10–20 hours per week)

Job Responsibility

Design, develop, and train AI/ML models to support video-related tasks (e.g., tagging, summarization, content understanding, or generation)
Work with existing datasets and create synthetic or labeled data where needed
Optimize model performance and deployment for efficiency and scalability
Collaborate with engineers and product leads to integrate AI features into the platform
Document your process, findings, and recommendations for future development

What we offer

Flexible remote setup
Short-term, well-scoped engagement with the potential for ongoing collaboration

Parttime

Senior Data Engineer - AI Focused

At Doctolib, we're on a mission to transform healthcare through the power of AI....

Location

France , Paris

Salary:

Not provided

Doctolib

Expiration Date

Until further notice

Requirements

Master’s or Ph.D. degree in Computer Science, Data Engineering, or a related field
5+ years of experience in Data Engineering, ideally supporting AI or ML workloads
Strong experience with the GCP data ecosystem
Proficiency in Python and SQL, with experience in data pipeline orchestration (e.g., Airflow, Dagster, Cloud Composer)
Deep understanding of NoSQL systems (e.g., MongoDB) and vector databases (e.g., FAISS, Vector Search)
Experience designing data architectures for RAG, embeddings, or model training pipelines
Knowledge of data governance, security, and compliance for sensitive or regulated data
Familiarity with W&B / MLflow / Braintrust / DVC for experiment tracking and dataset versioning (extract snapshots, change tracking, reproducibility)
Familiarity with containerized environments (Docker, Kubernetes) and CI/CD for data workflows
A collaborative mindset and passion for building the data foundations of next-generation AI systems

Job Responsibility

Ensure high standards of data quality for AI model inputs
Design, build, and maintain scalable data pipelines on Google Cloud Platform (GCP) for AI and machine learning use cases
Implement data ingestion and transformation frameworks that power Retrieval systems and training datasets for LLMs and multimodal models
Architect and manage NoSQL and Vector Databases to store and retrieve embeddings, documents, and model inputs efficiently
Collaborate with ML and platform teams to define data schemas, partitioning strategies, and governance rules that ensure privacy, scalability, and reliability
Integrate unstructured and structured data sources (text, speech, image, documents, metadata) into unified data models ready for AI consumption
Optimize performance and cost of data pipelines using GCP native services (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Vertex AI)
Contribute to data quality and lineage frameworks, ensuring AI models are trained on validated, auditable, and compliant datasets
Continuously evaluate and improve our data stack to accelerate AI experimentation and deployment

What we offer

Free comprehensive health insurance for you and your children
Parent Care Program: additional leave on top of the legal parental leave
Free mental health and coaching services through our partner Moka.care
For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy
Work Council subsidy to refund part of a sport club membership or a creative class
Up to 14 days of RTT
Lunch voucher with Swile card

Fulltime

Software & Data Engineer Intern

Join Entalpic's Platform team and contribute to the core software foundations of...

Location

France , Paris

Salary:

Not provided

Breega

Expiration Date

Until further notice

Requirements

Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or a related field
Strong interest in data engineering, data systems, and infrastructure for machine learning or scientific applications
Proficiency in Python and familiarity with at least one other programming language is a plus
Foundational knowledge of SQL and relational databases, with curiosity about NoSQL systems
Understanding of core data concepts such as ETL, data modeling, and data pipelines
Must be comfortable working in English in a technical environment
Motivated, curious, and eager to learn in a fast-paced startup setting

Job Responsibility

Data Engineering Implementation: Help build and maintain data pipelines that process and integrate multimodal data including simulation results, scientific text, and experimental measurements
Data Storage and Organization: Contribute to the implementation and organization of data storage solutions, ensuring data is well-structured, accessible, and documented
Automation and Tooling: Write scripts to automate data ingestion, cleaning, and transformation tasks under the guidance of senior engineers
Data Visualization and Analytics: Support the creation of basic data visualizations and analytical dashboards to help teams explore datasets, monitor data quality, and gain insights from experimental, simulation, and textual data
Applied ML Research: Prototype end-to-end pipelines using state-of-the-art LLMs for chemical entity extraction and explore ranking methods to improve data quality and retrieval for downstream AI systems
Data Quality and Documentation: Assist with data validation, basic lineage tracking, and documentation to improve data reliability and reproducibility
Infrastructure Collaboration: Work with data engineers, data scientists, and DevOps to understand how data systems are deployed and scaled on cloud platforms such as AWS or GCP
Cross-team Collaboration: Interact with scientists and engineers to understand data needs and help translate them into practical data solutions

What we offer

Competitive salary + full reimbursement of your transport card
Flexible work environment: Remote-Friendly with a minimum of 3 days in Paris offices per week (Station F)
1 paid day off per month
Professional development opportunities: access to conferences and internal learning sessions

Fulltime

Multimodal AI Engineer, Document Understanding

LlamaIndex

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
December 10, 2025

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Multimodal AI Engineer, Document Understanding

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Job Posted:December 10, 2025

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