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Vector Databases Jobs in Maywood, CA (NOW HIRING)

Senior Data Engineer

Long Beach, CA · On-site

$143K - $203K/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 ...

AI Engineer

Pasadena, CA · On-site

$125K/yr

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

AI Engineer

Pasadena, CA · On-site

$130K/yr

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

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

Senior AI Engineer

Pasadena, CA · On-site

$200 - $250/hr

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

Senior Data Engineer

Long Beach, CA · On-site

$111K - $151K/yr

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

Ai Engineer

Glendale, CA · On-site

$80 - $100/hr

Implement retrieval and embedding workflows (RAG, vector databases) for scalable knowledge retrieval. Apply software engineering best practices--testing, version control, and code review. * Business ...

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 ...

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 ...

Production experience with LLMs, RAG, vector databases, AI agents. * Experience owning projects independently from start to finish. * Direct experience working with internal business teams. * Recent ...

Hands-on with GenAI/LLMs, RAG, vector databases, and semantic search ; familiar with agents, A2A, MCP, and tool calling (or eager to go deep fast). * Strong .NET and Python - APIs, backend, and AI ...

Vector databases * Prompt engineering and evaluation * WebRTC, SIP, RTP, or telephony integrations * Azure AI, Azure OpenAI, or other cloud AI services * Docker and Kubernetes CI/CD pipelines and ...

Senior Solutions Architect

Burbank, CA · On-site

$150 - $200/hr

OCR/NLP; vector databases/search; microservices; IaC (Terraform); containers/Kubernetes; CI/CD; observability (OpenTelemetry). * Architecture frameworks (e.g., TOGAF) and cloud certifications (AWS ...

Vector databases and RAG patterns (indexing, chunking, embeddings, retrieval). * LLM integration (OpenAI, Azure OpenAI, Anthropic, or open‑source models) with prompt design, safety/guardrails, and ...

Showing results 21-40

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:

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.

Senior Data Engineer

Vast

Long Beach, CA • On-site

$143K - $203K/yr

Full-time

Re-posted 8 days ago


Job description

Vast is looking for a Senior Data Engineer, reporting to the Senior Director of Information Systems, to support the development of the data infrastructure and AI-driven capabilities that will be required for the design and build of artificial-gravity human-rated space stations.

This will be a full-time, exempt position located in our Long Beach location.

Responsibilities:

  • Design, architect, and implement scalable enterprise data infrastructure including data lakes, warehouses, and real-time streaming platforms
  • Build and maintain robust data pipelines that feed internal AI/ML tools and enable advanced analytics across all departments
  • Own end-to-end data architecture from ingestion through transformation to consumption, ensuring data quality, reliability, and security
  • Integrate data from complex engineering systems (PLM/Teamcenter), manufacturing systems (MES/MOM), ERP (NetSuite), IoT/sensor networks and other enterprise systems
  • Create innovative data solutions that enable AI/ML capabilities for engineering analysis, manufacturing optimization, and supply chain intelligence
  • Establish data governance frameworks, standards, and best practices across the organization
  • Implement MLOps infrastructure to support model training, deployment, and monitoring
  • Build real-time data pipelines from shop floor systems, test equipment, and operational technology (OT) environments
  • Collaborate with Engineering, Manufacturing, Supply Chain, and business teams to understand data requirements and deliver BI/AI-ready datasets
  • Lead and mentor a high-performing data engineering team, establishing technical standards and fostering a culture of extreme ownership
  • 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 scalability
  • Implement monitoring, alerting, observability, and disaster recovery capabilities for mission-critical data systems
  • Provide technical leadership and strategic guidance on data architecture to executive leadership

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Data Engineering, Computer Engineering, or equivalent work experience
  • 4+ years of hands-on experience in data engineering, data architecture, or related fields
  • 1+ years of experience in a technical leadership role leading data engineering teams or initiatives
  • Proven track record of building enterprise-scale data infrastructure and production data pipelines
  • Expert-level proficiency in SQL and Python
  • Deep hands-on experience with cloud data platforms (AWS, Azure, or GCP) and associated data services
  • Strong experience with modern data processing frameworks (Apache Spark, Kafka, Airflow, or equivalent)
  • Demonstrated experience with data warehousing technologies (Snowflake, Databricks, BigQuery, Redshift, or similar)
  • Experience supporting AI/ML initiatives with production-grade data pipelines and infrastructure

Preferred Skills & Experience:

  • Experience in manufacturing, aerospace, defense, or hardware-intensive industries
  • Background integrating data from PLM systems (Teamcenter, Windchill), ERP systems (NetSuite, SAP), and MES/manufacturing execution systems
  • Hands-on experience with MLOps tools, feature stores, and machine learning data pipelines
  • Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes)
  • Experience with real-time streaming architectures and event-driven systems
  • Familiarity with vector databases, knowledge graphs, and AI/LLM data architectures
  • Understanding of dimensional modeling, data vault methodology, and modern data architecture patterns
  • Contributions to open-source data engineering projects
  • Experience with digital twin architectures or simulation data management
  • Strong understanding of data security, compliance, and governance in regulated industries
  • Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders
  • Proven ability to balance strategic vision with tactical execution in fast-paced startup environments
  • Track record of extreme ownership-proactively identifying problems and driving solutions to completion

Additional Requirements:

  • Ability to travel up to 10% of the time to other Vast facilities or vendor sites
  • Willingness to work extended hours or weekends to support critical mission milestones and production launches
  • Must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain required authorizations from the U.S. Department of State (export control requirement)

Pay Range:

  • Senior Data Engineer: $143,000.00  -  $203,000.00