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Vector Databases Jobs in Garden Grove, CA (NOW HIRING)

Confie

AI Engineer

Huntington Beach, CA · On-site

$100 - $140/hr

Build advanced RAG systems with vector databases, hybrid search (dense + sparse retrieval), and reranking for domain-specific chatbots and knowledge retrieval. Develop generative AI solutions for ...

Saransh Inc

AI/ML Architect

Irvine, CA · On-site

$68.50 - $88/hr

Strong expertise in retrieval-based systems (RAG, vector databases, embeddings, indexing) * Experience with API development and backend system integration. * AWS cloud-native development experience

Vast

Staff Data Architect

Long Beach, CA

$155K - $221K/yr

Evaluate and implement cutting-edge data technologies including cloud-native services, vector databases, and modern data stack tools * Optimize data pipelines for performance, cost-efficiency, and ...

Vast

Staff Data Architect

Long Beach, CA · On-site

$67 - $86.25/hr

Familiarity with vector databases, knowledge graphs, and AI/LLM data architectures * Understanding of dimensional modeling, data vault methodology, and modern data architecture patterns

Samba

Principal, Insights & Innovation

Los Angeles, CA · On-site

$160K - $180K/yr

Incorporate AI and agentic workflows into internal and external solutions, including approaches such as data embeddings, vector databases, and multimodal models. * Supporting thought leadership and ...

Boot Barn

Data Scientist

Irvine, CA · On-site

$95K - $120K/yr

Collaborate with Data and AI/ML Engineers to establish RAG pipelines, vector databases, and agentic frameworks. * Prototype and deploy generative AI applications such as content generation agents ...

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Showing results 21-40

All JobsVector Databases JobsVector Databases Jobs in Garden Grove, 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 are popular job titles related to Vector Databases jobs in Garden Grove, CA?

For Vector Databases jobs in Garden Grove, CA, the most frequently searched job titles are:

What job categories do people searching Vector Databases jobs in Garden Grove, CA look for?

The top searched job categories for Vector Databases jobs in Garden Grove, CA are:

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

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

Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Garden Grove, CA as of August 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 64% In-person, and 36% Remote job distribution.

Applied AI Staff Engineer - Remote / Telecommute

CYNET SYSTEMS

Aliso Viejo, CA • Remote

$65 - $70/hr

Contractor

Medical, Dental, Vision, Life, Retirement

Posted 11 days ago

Job description

Job Overview:

Pay Range: $65.00hr - $70.00hr

Requirement/Must Have:

  • Lead technical strategy for AI/LLM systems across multiple products.
  • Proven expertise in Python and ML frameworks such as MLFlow, TensorFlow, PyTorch, and Scikit-learn.
  • Strong background in statistical analysis, data exploration, and working with large-scale datasets.
  • Experience with feature engineering, data preprocessing, and data management.
  • 3+ years of hands-on experience in machine learning, data science, search relevance, or ranking systems.
  • Strong experience building and maintaining production-grade backend applications.
  • Experience designing and developing RESTful APIs and distributed systems.
  • Strong SQL skills and experience working with relational databases.
  • Solid understanding of data engineering fundamentals, including data quality, validation, transformation, modeling, and efficient storage.
  • Experience with cloud platforms such as Google Cloud Platform (GCP) or AWS.
  • Experience using Docker, Git, CI/CD pipelines, automated testing frameworks, and modern software engineering best practices.
  • Proficiency in Python, REST API, Pandas, and NumPy.
  • Experience with AWS Services, GCP, Kubernetes, and Bedrock.
  • Experience with event-driven architectures, including Kafka.
  • Experience with orchestration frameworks such as LangGraph, LangChain, and AirFlow.
  • Experience with Vector Databases like Qdrant.

Responsibilities:

  • Lead technical strategy for AI/LLM systems across multiple products.
  • Architect retrieval, orchestration, agentic, and evaluation systems that run reliably in production.
  • Set the standards for AI safety, evaluation, observability, and responsible rollout in a regulated context.
  • Mentor junior-level engineers into strong AI engineers.
  • Employ AI Native development skills to multiply productivity using tools like Claude.
  • Evaluate new models, techniques, and tools to implement within the team.
  • Design, develop, and maintain scalable Python applications and backend services.
  • Build systems that ingest, validate, transform, and manage structured and unstructured data in production environments.
  • Design data models and storage solutions that support scalable, high-performance applications.
  • Develop reusable components for data processing, validation, enrichment, and feature generation.

Nice to Have:

  • Experience with Kubernetes and container orchestration.
  • Familiarity with event-driven architectures and messaging platforms such as Kafka.
  • Familiarity with ML model deployment and inference pipelines.

Skills:

  • AIML.
  • Python.
  • MLFlow.
  • TensorFlow.
  • PyTorch.
  • Scikit-learn.
  • RESTful APIs.
  • SQL.
  • AWS.
  • GCP.
  • Docker.
  • Kubernetes.
  • Kafka.
  • LangChain.
  • Vector Databases.

Qualification And Education:

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related quantitative field.
  • 10+ years of software engineering experience, with deep recent time leading production AI/LLM systems.

Benefits
 
Our Benefits Include:
  • Medical, Dental, and Vision Insurance
  • 401(k) Retirement Plan
  • Health Savings Account (HSA)
  • Disability Insurance (Short-Term and Long-Term)
  • Life and AD&D Insurance
  • Paid Sick Leave (where required by applicable state or local law)
  • Supplemental Insurance Plans
  • Identity Theft Protection
  • Pet Insurance
  • Employee Wellness Programs
  • Employee Assistance Program (EAP)
  • Career Growth and Professional Development Opportunities
Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.

About Cynet Systems

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.
As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Cynet Systems logo

About Cynet Systems

Sourced by ZipRecruiter

Cynet Systems Inc is a staffing and recruiting corporation nestled in Ashburn, VA, USA. Established in 2010, the company operates within the Information Technology and Services sector, specializing in providing effective workforce solutions to different business needs, including IT consulting, direct hire, and contract staffing services. Through the years, Cynet Systems has built an impressive portfolio, going beyond borders and expanding its operations internationally in Canada and India. Rooted in its core values of teamwork, leadership, and commitment, Cynet Systems helps businesses unlock their full potential by providing versatile and competent professionals that perfectly align with their needs. Fueled by their unwavering mission to deliver top-tier talent to businesses worldwide, Cynet Systems garnered various recognitions including SIA's fastest-growing staffing firms and Best Place to Work in Virginia for 2019.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Sterling, VA, US

Year founded

2010

Social media

Twitter

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