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Vector Databases Jobs in Maywood, CA (NOW HIRING)

Nowcom

AI Voice Engineer

Los Angeles, CA · On-site

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 ...

ACCO Engineered Systems

Senior Developer, AI

Pasadena, CA · On-site

$59.50 - $78.50/hr

Hands-on experience with vector databases and semantic search technologies * Strong expertise with LLM orchestration frameworks (e.g., Semantic Kernel, LangChain, LlamaIndex, AutoGen). * Proven track ...

ACCO Engineered Systems

Senior Developer, AI

Pasadena, CA · On-site

$59.50 - $78.50/hr

Hands-on experience with vector databases and semantic search technologies * Strong expertise with LLM orchestration frameworks (e.g., Semantic Kernel, LangChain, LlamaIndex, AutoGen). * Proven track ...

ACCO Engineered Systems

Senior Developer, AI

Pasadena, CA · On-site

$59.50 - $78.50/hr

Hands-on experience with vector databases and semantic search technologies * Strong expertise with LLM orchestration frameworks (e.g., Semantic Kernel, LangChain, LlamaIndex, AutoGen). * Proven track ...

Hop

Senior AI Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

Hands-on fine-tuning of foundation models; comfort with MLflow, Ray/KubeRay, and vector databases. * Deep familiarity with cloud warehouses (BigQuery, Redshift), lake formats (Parquet, Avro), and ...

CompassX Group

Solution Architect - GenAI

Los Angeles, CA · On-site

$150 - $200/hr

LLM APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock), vector databases, RAG pipelines, evaluation frameworks, and deployment infrastructure. * Bridge to Enterprise Systems: Integrate GenAI ...

Luxoft

AI Technical Lead

Los Angeles, CA · On-site

$200 - $250/hr

Oversee the development of enterprise Retrieval-Augmented Generation (RAG) pipelines, semantic chunking strategies, and vector database integrations. * Implement strict evaluation and observability ...

Disney Experiences

Sr Software Engineer

Glendale, CA

$135K - $181K/yr

Experience with RAG (Retrieval Augmented Generation), vector databases, and embeddings * Excellent programming skills in languages Java and Python. * Experience with cloud platforms (AWS, GCP, or ...

CreatorIQ, Inc

ML Engineer

Los Angeles, CA · On-site

$132K - $165K/yr

Experience with vector databases or retrieval systems at scale * Experience with managed ML services on AWS (SageMaker) and/or GCP (Vertex AI) * Annotation workflow experience (Label Studio, Scale AI ...

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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.

AI Voice Engineer

Nowcom

Los Angeles, CA • On-site

Full-time

Posted 28 days ago

Job description

This role involves working with state-of-the-art speech recognition, speech synthesis, voice streaming, and AI agent frameworks to create scalable voice solutions for customer service, sales, finance, and automation applications. This is an on-site position with no relocation assistance provided.
If you're passionate about conversational AI and enjoy solving challenging engineering problems, we'd love to hear from you.
  • Responsibilities
    • Design and develop real-time voice-to-voice AI agents.
    • Build conversational AI systems using LLMs and agent frameworks.
    • Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies into production applications.
    • Optimize latency and streaming performance for natural conversations.
    • Develop backend services and APIs using Python and C#/.NET.
    • Integrate with telephony, voice streaming, and communication platforms.
    • Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows.
    • Collaborate with product managers, AI engineers, and software developers to deliver production-ready AI solutions.
    • Evaluate emerging AI models, speech technologies, and voice platforms.
    • Monitor, troubleshoot, and continuously improve voice agent performance and reliability.

    Required Qualifications
    • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
    • 5+ years of professional software engineering experience.
    • Hands-on experience building voice-to-voice AI applications.
    • Strong understanding of:

      • Speech Recognition (Automatic Speech Recognition - ASR)
      • Speech Synthesis (Text-to-Speech - TTS)
      • Voice Activity Detection (VAD)
      • Audio streaming and low-latency communication

    • Professional experience with Python and C#/.NET.
    • Experience consuming AI APIs and working with LLMs.
    • Experience building REST APIs and microservices.
    • Knowledge of asynchronous programming, event-driven architectures, and real-time streaming.
    • Strong debugging, analytical, and problem-solving skills.

    Preferred Qualifications
    Experience with one or more of the following:
    • Real-time conversational AI platforms
    • AI agent frameworks
    • Retrieval-Augmented Generation (RAG)
    • 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 cloud-native application development

Equal Opportunity Employer
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For further information, please review the Know Your Rights notice from the Department of Labor.

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