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Vector Databases Jobs in California (NOW HIRING)

Kai Cyber, Inc.

Senior Data Engineer, AI Platform

San Jose, CA · On-site

$124K - $168K/yr

Familiarity with vector databases and ANN search systems * Experience in data systems for AI platforms or ML infrastructure * Background in search, recommendation systems, or information retrieval ...

K-Tek Resourcing LLC

Python Engineer

San Jose, CA

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 Developer

San Jose, CA

$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 ...

Zilliz

Solutions Architect - SF Bay Area

Redwood City, CA

$77.25 - $101.50/hr

Zilliz is a fast-growing startup developing the industry's leading vector database company 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

$250K - $285K/yr

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

Diverse Lynx

Python Engineer

San Jose, CA

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

Apple

AI Data Engineer

Cupertino, CA

$203K - $305K/yr

You will design and implement data pipelines that ingest from legal systems, transform data into AI-ready formats, load vector databases and other AI stores, and expose data services through APIs.

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 company for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector ...

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 ...

Programmers.io

Java Full Stack AI Developer

Sunnyvale, CA · On-site

$61.50 - $79.50/hr

• Drive the adoption of embedded AI, moving beyond simple API calls to integrating local LLMs and vector databases into the application layer. Evangelize usage of AI tools to accelerate developer ...

eTeam

Senior AI/ML Engineer

Sunnyvale, CA · On-site

$122K - $167K/yr

... vector databases and semantic search • Knowledge of responsible AI, data ethics, and bias mitigation • Experience in client-facing delivery environments • Familiarity with API development and ...

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 ...

MGT Insurance

Senior Agentic Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Responsibilities : • Lead the design and implementation of multi-agent systems using LLMs, vector databases, and agent orchestration frameworks to create intelligent, goal-oriented automation. • ...

Trulioo

Data Platform Engineer

San Diego, CA · On-site

$120K - $150K/yr

Work with Vector Databases (e.g., AWS S3 Vector, PostgresVectorDb, OpenSearch) to support similarity and semantic search applications. * Collaborate with data scientists, software engineers, and ...

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All JobsVector Databases JobsVector Databases Jobs in California

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 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 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 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
Senior Site Reliability Engineer Cloud Platform

Senior Site Reliability Engineer Cloud Platform

Zilliz

Redwood City, CA • On-site

$69.75 - $92.75/hr

Full-time

Posted 18 days ago

Job description

Zilliz is a fast-growing startup developing the industry’s leading vector database company for enterprise-grade AI. Founded by the engineers behind Milvus, the world’s most popular open-source vector database, the company builds next-generation database technologies to help organizations quickly create AI applications. On a mission to democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization.
What you will do:
  • Work at the intersection of development and site reliability. Creating SRE tools and systems, as well as supporting existing infrastructure and platforms.
  • Ensure the reliability, availability, and performance of Zilliz’s distributed database systems.
  • Develop and implement strategies for monitoring, incident management, and disaster recovery.
  • Automate system operations and maintenance tasks to improve efficiency and reduce manual intervention.
  • Design and build tools to manage and monitor infrastructure, ensuring scalability and robustness.
  • Collaborate with software engineers to enhance system reliability, scalability, and performance.
  • Maintain and improve the CI/CD pipeline to ensure smooth and rapid deployment of changes.
  • Actively contribute to the Milvus Vector Database open-source community, focusing on improving reliability and operational efficiency.
What we are looking for:
  • 4+ years of experience in site reliability engineering or similar roles with a focus on cloud-native systems.
  • Proficiency in scripting languages such as Python, Go, or Java.
  • Strong knowledge of container orchestration technologies like Kubernetes and Docker.
  • Expertise with cloud platforms such as AWS, GCP, or Azure, and their respective monitoring and management tools.
  • Experience with infrastructure as code tools such as Terraform or Ansible.
  • Familiarity with CI/CD tools such as Jenkins, GitLab CI, or Argo.
  • Proven ability to troubleshoot complex distributed systems and resolve issues promptly.
  • Bachelor’s degree or above in computer science, software engineering, or other relevant disciplines.
  • Ability to thrive in a fast-paced, startup environment and handle multiple projects simultaneously.
  • Experience with Open Source Milvus Vector Database is nice to have
Zilliz is an Equal Opportunity Employer and welcome people from all backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment regardless of race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.