ZipRecruiter

Log In

1

Vector Databases Jobs in California (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 ...

Cynet Systems

Python Backend Developer

San Jose, CA · On-site

$60 - $65/hr

Experience with vector databases such as Pinecone or Weaviate. * Familiarity with AI workflow frameworks such as LangChain or Llama Index. * Experience with Docker and cloud platforms such as AWS or ...

VDart, Inc.

Python Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/Google Cloud ...

K-Tek Resourcing LLC

Python Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/Google Cloud ...

TechnoSphere, Inc.

Python Engineer

San Jose, CA · On-site

$10/hr

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Carter Support Services

AI/ML Engineer

Burbank, CA · On-site

... vector databases or MongoDB • Ensure CI/CD integration and cloud deployment (Azure preferred) • Establish observability, monitoring, and evaluation frameworks for AI systems • Collaborate cross ...

E-Solutions

AI Application Architect

Encino, CA · On-site

Vector databases / vector search * Embeddings and semantic search * Prompt engineering and optimization * AI orchestration frameworks * Multi-agent workflows * Context management strategies * AI ...

K-Tek Resourcing LLC

Python Developer

San Jose, CA · On-site

$59 - $81.25/hr

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/Google Cloud ...

Diverse Lynx

Python Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Diverse Lynx

Python Backend Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). * Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Zilliz

Solutions Architect - SF Bay Area

Redwood City, CA · On-site

$250K - $285K/yr

Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector ...

Zilliz

Solutions Architect - SF Bay Area

Redwood City, CA · On-site

$77.25 - $101.50/hr

Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector ...

next page

Showing results 1-20

All JobsVector Databases JobsVector Databases Jobs in California

Vector Databases information

What is the salary of a vector database developer?

The salary of a vector database developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Skilled developers with expertise in machine learning, data structures, and database management may earn higher salaries, especially in tech hubs or with advanced certifications.

Are vector databases the future?

Vector database jobs involve managing and optimizing databases designed for high-dimensional vector data, which are essential for AI and machine learning applications. As AI continues to grow, demand for professionals skilled in vector database technologies and related tools like embedding models is expected to increase, making this a promising field for future job opportunities.

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 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 can you do with a vector database?

A vector database is used in roles involving data management and machine learning to store, search, and retrieve high-dimensional vector representations of data such as images, text, or audio. It enables efficient similarity searches, supporting applications like recommendation systems, natural language processing, and computer vision. Working with a vector database often requires knowledge of data structures, indexing techniques, and programming skills in languages like Python or C++.

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 are the top 5 vector databases?

Top vector databases used in data management and AI applications include Pinecone, Weaviate, FAISS, Milvus, and Annoy. These databases are optimized for storing and searching high-dimensional vector data, often requiring skills in machine learning and database management. They are widely adopted for tasks like similarity search and recommendation systems.
What are popular job titles related to Vector Databases jobs in California? For Vector Databases jobs in California, the most frequently searched job titles are:
What job categories do people searching Vector Databases jobs in California look for? The top searched job categories for Vector Databases jobs in California are:
What cities in California are hiring for Vector Databases jobs? Cities in California with the most Vector Databases job openings:
Vector Databases jobs near you

AI/ML Engineer

Carter Support Services

Burbank, CA • On-site

$111K - $153K/yr

Full-time

Posted 14 days ago

Job description

Location: Burbank, CA (100% Onsite)
Job Type: Full-Time
Experience Level: Mid-Senior (10+ Years)
Industry: Information Technology & Services

Position Overview

Carter Support Services is seeking a highly experienced Senior AI/ML Engineer to design, develop, and deploy advanced AI solutions. This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows.

The ideal candidate will bring deep expertise in Python, cloud-based AI deployment (Azure), and modern NLP techniques, along with experience delivering production-grade AI systems.

Key Responsibilities
  • Design and implement AI/ML solutions using Python and modern ML frameworks
  • Develop and optimize prompt engineering strategies for LLM-based systems
  • Build and deploy RAG (Retrieval-Augmented Generation) pipelines
  • Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications
  • Develop and orchestrate agentic AI workflows with tool/function calling
  • Implement vector search solutions using vector databases or MongoDB
  • Ensure CI/CD integration and cloud deployment (Azure preferred)
  • Establish observability, monitoring, and evaluation frameworks for AI systems
  • Collaborate cross-functionally to deliver production-ready AI features
Required Qualifications
  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 10+ years of experience in software engineering or AI/ML roles
  • 7+ years of Python experience (expert-level proficiency required)
  • 7+ years of Microsoft Azure experience, including Azure Machine Learning
  • 7+ years of DevOps experience, including CI/CD pipelines
  • 7+ years of MongoDB or similar database experience
  • Strong experience with LLM integration and RAG architectures
  • Experience with prompt engineering and context optimization
  • Solid understanding of NLP and transformer-based models
  • Experience with vector databases and search systems
  • Familiarity with agentic AI workflows and tool/function calling
Preferred Qualifications
  • Experience with Azure OpenAI API
  • Experience building scalable, enterprise-grade AI applications
  • Background in AI system monitoring, evaluation, and optimization
Work Environment
  • 100% onsite role in Burbank, CA
  • Collaborative, fast-paced technical environment

Powered by JazzHR

JruqlLdXda