Top 127 Vector database azure cloud cloud research Jobs

AI Engineer
Better Direct —Tempe, AZ
- $60,000 - $80,000 a year
- Full-time
- Background check
- Azure
- System design
Quick Apply
Data Architect
Farm Credit Financial Partners —Springfield, MA
- Overtime
- Hybrid work
- Computer Science
- 5 years
- Research
- Tuition reimbursement
- 401(k) matching
AI Research Scientist
Gallup —Omaha, NE
- $165,000 - $225,000 a year
- Hybrid work
- Azure
- Computer Science
- Mid-level
- Health insurance
- Dental insurance
Systems Engineer - AI Integration - TS/SCI with Polygraph
General Dynamics Information Technology —Herndon, VA
- $187,000 - $253,000 a year
- Computer Science
- Research
- 8 years
Staff Software Engineer, Scientific System of Record
Lila Sciences —Cambridge, MA
- $144,000 - $288,000 a year
- Remote
- Azure
- 6 years
- Computer Science
Quick Apply
Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior
EY —Manayunk, PA
- $65,500 - $152,100 a year
- System design
- Research
- Driver's License
- Paid holidays
- Health insurance
Senior Python Backend Engineer
AIAEC LLC —Phoenix, AZ
- Civil engineering
- Azure
- 5 years
Quick Apply
Full Stack Developer, Associate
LCG, Inc. —Bethesda, MD
- Computer Science
- Mid-level
- SQL
- Paid holidays
- Disability insurance
Quick Apply
Principal Partner Solution Architect
TiDB —Remote
- Remote
- Azure
- System design
- AWS
- Paid holidays
- Parental leave
Quick Apply
AI/ML and Data Engineer
SME —Southfield, MI
- $138,000 - $172,000 a year
- Computer science
- Azure
- Computer Science
- 403(b) matching
- Paid holidays
Quick Apply
Artificial Intelligence/ Machine Learning Developer
Unissant —Ashburn, VA
- Extended hours
- Azure
- Computer Science
- Research
Quick Apply
Sr. Machine Learning Ops Engineer
CIM Group, LP —Los Angeles, CA
- $175,000 - $225,000 a year
- Full-time
- 7 years
- Azure
- Computer Science
- Wellness program
- Paid parental leave
Quick Apply
Sr. Consultant, Cloud Solutions
Burwood Group, Inc —Chicago, IL
- Full-time
- Remote
- Azure
- DevOps
- AWS
Quick Apply
AI Engineer
CoreStory —Remote
- Remote
- Azure
- 3 years
- AWS
Senior AI Developer
Gene by Gene —Houston, TX
- Full-time
- Hybrid work
- Computer science
- Computer Science
- 3 years
- Health savings account
- Disability insurance
Quick Apply
11d
Cybersecurity Analyst - SSB
SkyePoint Decisions —Arlington, VA
- $90,000 - $103,000 a year
- Customer service
- 5 years
- Mid-level
- Health savings account
- Disability insurance
Quick Apply
8d
Innovations and AI Solutions Engineer
Wilson, Sonsini, Goodrich & Rosati —Austin, TX
- $105,400 - $158,125 a year
- Hybrid work
- Computer science
- Microsoft Access
- Computer Science
Software Engineer, Database Systems
OpenAI —San Francisco, CA
- $230,000 - $385,000 a year
- Full-time
- Azure
- System design
- Mid-level
Senior Manager, DevSecOps
DoubleVerify —New York, NY
- $131,000 - $260,000 a year
- Computer science
- Computer Science
- 5 years
Quick Apply
Full Stack- FDE EST
NewPage Digital Healthcare Solutions —Remote
- Contract
- Remote
- Azure
- Computer Science
- 3 years
3d

I want to receive the latest job alert for vector database azure cloud cloud research

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

vector database azure cloud cloud research jobs near

AI Engineer

Better Direct -
Tempe, AZ

Quick Apply

Job Details

Full-time
$60,000 - $80,000 a year

Qualifications

AI models
Index optimization
TensorFlow
Data transformation pipeline development
NumPy
Generative models
AI platforms (beyond public GPTs)
Computational framework
Pandas
Machine intelligence
GitHub
Neural networks
Metadata
Benchmarking
Machine learning libraries
Model evaluation
Machine learning frameworks

Full Job Description

About the Role

We are looking for a motivated AI Engineer who is passionate about large language models (LLMs), machine learning, and applied AI systems. This position is focused on building real-world AI systems, not just experimenting with models.

You will work on projects involving open-source LLMs, retrieval-augmented generation (RAG) pipelines, vector databases, and AI-powered document processing systems. The goal is to build scalable AI workflows that solve practical problems such as knowledge retrieval, document analysis, and AI-assisted automation.

This role is ideal for engineers who want hands-on experience deploying AI systems used in production-like environments.

Responsibilities

AI & Machine Learning Development

Build and experiment with open-source LLM and SLM pipelines.
Design and implement Retrieval Augmented Generation (RAG) systems.
Develop AI pipelines capable of processing documents, PDFs, and structured data.
Work with embedding models and vector search systems.
Implement prompt engineering, model evaluation, and response optimization.
Assist with fine-tuning or adapting open-source models when necessary.

Data Processing & AI Pipelines

Build ingestion pipelines for PDFs, documents, and datasets.
Implement document chunking, embedding generation, and indexing strategies.
Work with vector databases to support semantic search and retrieval.
Optimize pipelines for latency, scalability, and cost efficiency.

Research & Experimentation

Evaluate different open-source models and architectures.
Compare embedding models and retrieval methods.
Test improvements in RAG performance and hallucination reduction.
Explore emerging techniques in Vision Language Models (VLMs).

Collaboration

Work with engineers to integrate AI components into applications.
Document experiments and technical findings.
Participate in weekly discussions on AI architecture decisions and improvements.

Required Skills & Knowledge

Core AI Knowledge

Strong understanding of:
Machine Learning
Neural Networks
Deep Learning fundamentals
Familiarity with:
Large Language Models (LLMs)
Small Language Models (SLMs)

Programming

Strong proficiency in Python
Experience with AI/ML frameworks such as:
PyTorch
TensorFlow
Hugging Face Transformers

AI Application Frameworks

Experience with:

LangChain or similar orchestration frameworks
Prompt engineering and AI workflow building

Vector Databases

Conceptual and practical understanding of any vector databases such as:

Pinecone
ChromaDB
Milvus
Qdrant
FAISS
Weaviate

Understanding of:

embeddings
similarity search
indexing strategies
metadata filtering

RAG Systems

Ability to design or understand:

Retrieval pipelines
Document chunking strategies
Embedding pipelines
Hybrid search
Context window optimization
RAG evaluation methods

Data Processing

Experience with:

PDF extraction
Document parsing pipelines
Data preprocessing

Bonus Knowledge

Vision Language Models (VLMs)
Multimodal AI systems
Distributed AI inference
GPU inference optimization

Preferred Project Experience

Candidates should have completed at least 1–3 hands-on AI projects, such as:

Example Project 1 – RAG Knowledge Assistant

Built a chatbot that answers questions from internal documentation.
Implemented document ingestion, chunking, embedding generation, and vector search.
Used LangChain + vector database + open-source LLM.

Example Project 2 – Document AI System

Created a system that extracts structured information from PDFs.
Built pipelines for PDF parsing → embeddings → AI summarization.

Example Project 3 – AI Research Experiment

Compared multiple embedding models and evaluated search accuracy.
Benchmarked RAG response quality and hallucination rates.

Example Project 4 – LLM Application

Built a real-world tool using open-source models (e.g., summarizer, Q&A system, coding assistant).

Real-World Experience

Candidates may also have experience such as:

Contributing to open-source AI projects
Participating in AI hackathons
Research experience in machine learning or NLP
Building production-style AI APIs
Deploying models using Docker or cloud platforms
Working with LLM inference servers (vLLM, TGI, Ollama, etc.)

Tools & Technologies (Exposure Preferred)

AI / ML

PyTorch
Hugging Face
Transformers
Sentence Transformers

LLM Tools

LangChain
LlamaIndex
Open-source LLMs (LLaMA, Mistral, etc.)

Vector Databases

Pinecone
ChromaDB
Milvus
Qdrant
FAISS
Weaviate

Data Tools

Pandas
NumPy

Deployment

Docker
REST APIs / FastAPI
Basic cloud exposure (AWS/GCP/Azure)

What You Will Gain

Hands-on experience building real AI systems
Exposure to modern LLM architecture and AI infrastructure
Experience with RAG pipelines and vector databases
Mentorship from engineers working in applied AI
Opportunity to contribute to real production-style AI tools

Candidate Profile

We are looking for someone who:

Is curious and loves experimenting with AI systems
Enjoys solving practical engineering problems
Can quickly learn new frameworks and models
Is comfortable reading research papers and technical documentation
Has strong problem-solving and debugging skills

Application Requirements

Please include:

Resume
GitHub profile (required)
Links to AI/ML projects
Brief description of a RAG or LLM system you have built

Pay: $60,000.00 - $80,000.00 per year

Work Location: In person

Quick Apply

Refine Your Search

vector database azure cloud cloud research jobs

AI Engineer

Data Architect

AI Research Scientist

Systems Engineer - AI Integration - TS/SCI with Polygraph

Staff Software Engineer, Scientific System of Record

Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior

Senior Python Backend Engineer

Full Stack Developer, Associate

Principal Partner Solution Architect

AI/ML and Data Engineer

Artificial Intelligence/ Machine Learning Developer

Sr. Machine Learning Ops Engineer

Sr. Consultant, Cloud Solutions

AI Engineer

Senior AI Developer

Cybersecurity Analyst - SSB

Innovations and AI Solutions Engineer

Software Engineer, Database Systems

Senior Manager, DevSecOps

Full Stack- FDE EST

I want to receive the latest job alert for vector database azure cloud cloud research

Related Searches

Explore jobs in more locations

Job Seeker Tools

Employer Tools

Browse

Stay Connected