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Vector Databases Jobs in Maywood, CA (NOW HIRING)

Carter Support Services

AI/ML Engineer

Burbank, CA · On-site

$111K - $153K/yr

Implement vector search solutions using vector databases or MongoDB * Ensure CI/CD integration and cloud deployment (Azure preferred) * Establish observability, monitoring, and evaluation frameworks ...

Carter Support Services

AI/ML Engineer

Burbank, CA · On-site

Implement vector search solutions using vector databases or MongoDB * Ensure CI/CD integration and cloud deployment (Azure preferred) * Establish observability, monitoring, and evaluation frameworks ...

Staffingine LLC

AI Architect

Torrance, CA · On-site

$65.75 - $86.75/hr

Develop advanced RAG pipelines leveraging vector databases Chroma DB Milvus FAISS and embedding strategies for contextual accuracy * Integrate AI capabilities with enterprise systems via REST and ...

The Bronx

Senior Full Stack AI Engineer

West Covina, CA · On-site

$150 - $200/hr

Develop AI-powered features involving LLMs, RAG, embeddings, vector databases, and AI agents as needed * Monitor and improve application reliability, performance, security, and cost QUALIFICATIONS ...

K&K Global Talent Solutions

Data Architect

Fountain Valley, CA · On-site

$69.25 - $89/hr

AI/ML capabilities covering Python, ML pipelines, MLOps, Generative AI, LLMs, RAG, embeddings, vector databases, LangChain/LangGraph and AI agents. * Experience applying AI to data quality automation ...

SCAN Group

Principal AI Architect

Lakewood, CA · On-site

$200 - $250/hr

Oversee vector database design (Azure AI Search or equivalent) and integration with Snowflake/Fabric data hubs.Implement high-availability, cost-optimized compute and storage strategies for AI ...

East West Bank

Senior AI Engineer

Pasadena, CA · On-site

$150K/yr

Practical experience with prompt engineering, RAG, embeddings, vector databases, LLM orchestration frameworks, agentic workflows, evaluation frameworks, and hallucination mitigation. * Ability to ...

East West Bank

AI Engineer

Pasadena, CA · On-site

Practical experience with prompt engineering, RAG, embeddings, vector databases, LLM orchestration frameworks, agentic workflows, evaluation frameworks, and hallucination mitigation. * Ability to ...

East West Bank

Senior AI Engineer

Pasadena, CA · On-site

$114K - $156K/yr

Practical experience with prompt engineering, RAG, embeddings, vector databases, LLM orchestration frameworks, agentic workflows, evaluation frameworks, and hallucination mitigation. * Ability to ...

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All JobsVector Databases JobsVector Databases Jobs in Maywood, CA

Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What are the key skills and qualifications needed to thrive as a vector database engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What cities near Maywood, CA are hiring for Vector Databases jobs?

Cities near Maywood, CA with the most Vector Databases job openings:

Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Maywood, CA as of August 2026, with employment types broken down into 62% Full Time, and 38% Contract. Highlights an 100% In-person job distribution.

A2A/ MCP Data Science Engineer

Amaze Systems

Los Angeles, CA • On-site

Other

Posted 5 days ago

Job description


We need only local /Nearby candidate - Woodland Hills, CA.

Mandatory Skills;

8+ years of Python development experience

5+ years of Machine Learning model development and training

3+ years of Generative AI / LLM solution development

3+ years of Vector Database, Embeddings, and RAG implementation

2+ years of A2A (Agent-to-Agent) and MCP (Model Context Protocol) implementation experience

2+ years of AI Agent and Multi-Agent System development experience

Top Mandatory Skills

Python (Expert Level)

Machine Learning Model Training & Fine-Tuning

Generative AI, LLMs, Prompt Engineering

A2A (Agent-to-Agent Communication) & MCP (Model Context Protocol)

Vector Databases, Embeddings, RAG & MongoDB

Document Extraction, Parsing & Chunking

AI Agent Development & Agent Orchestration Frameworks

Preferred Technology Stack

Python

LangChain / LangGraph

LlamaIndex

OpenAI / Azure OpenAI

MCP (Model Context Protocol)

A2A Agent Frameworks

Vector DBs (Pinecone, Chroma, Weaviate, Milvus, FAISS)

MongoDB

RAG Pipelines

Hugging Face

MLflow

FastAPI

Docker & Kubernetes

Domain Experience (If any ) – Good to have healthcare experience

Location -Woodland Hills, CA

Onsite Requirement - Onsite


Job Title: Lead II - ML Engineering Data Science Engineer Role Overview


  • We are seeking a highly skilled Data Science Engineer to design and develop scalable ML and Generative AI solutions.
  • The ideal candidate will have deep expertise in Python, hands-on experience in model training, document processing pipelines, and strong knowledge of vector databases and modern ML/GenAI frameworks.


Key Responsibilities

  • Develop and deploy machine learning and GenAI solutions using Python Design and optimize prompt engineering strategies for LLM-based applications
  • Build document extraction, parsing, and chunking pipelines for structured and unstructured data Train, evaluate, and fine-tune ML models; manage tagging and labeling workflows Implement embedding generation and vector search solutions
  • Integrate ML models with Vector DBs and MongoDB Ensure code quality, scalability, and production readiness


Required Qualifications

  • Expert-level proficiency in Python Strong experience in model training, evaluation, and tagging workflows
  • Hands-on experience with document extraction and chunking techniques
  • Solid understanding of ML algorithms and Generative AI concepts
  • Experience working with Vector Databases and/or MongoDB
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About Amaze Systems

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We strive to be the very best in our industry. We're the Best IT Specialists. We value our clients and their trust in us and hence, Our IT & Web Consultants don't hesitate to move mountains to give them high quality & innovative digital strategies, without resting, till they get the brand of their dreams. Our impeccable digital executions has helped several businesses multiply and increase their business enquiries substantially over years making us one of the most preferred online partners.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Dallas, TX, US

Social media

Twitter

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