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Vector Databases Jobs in Miami, FL (NOW HIRING)

Purple Drive

AI/ML Architect - RAG, LLM & Azure

Miami, FL · On-site

$60.75 - $79.25/hr

Vector databases (Pinecone, DB Vector, or similar) * LangChain, LlamaIndex, or similar orchestration frameworks * Embeddings and fine-tuning techniques * Experience with document chunking, knowledge ...

Intellisoft Technologies

Python Developer

Sunrise, FL · On-site

$63/hr

Integrate LLMs with mcp servers| vector databases| and observability systems for adaptive agentbehavior. Ensure reliability| performance| and maintainability through rigorous testing| type safety ...

E-Solutions

AWS AI Architect (AWS Bedrock Expertise

Miami, FL · On-site

$62 - $81.25/hr

Build Retrieval-Augmented Generation (RAG) pipelines using Amazon OpenSearch, Aurora ML Vector Engine, DynamoDB, or 3rd-party vector databases. * Evaluate foundation models (Claude, Llama, Amazon ...

United IT

Java & Python Engineer

Sunrise, FL · On-site

Integrate LLMs with mcp servers, vector databases, and observability systems for adaptive agent behavior. * Ensure reliability, performance, and maintainability through rigorous testing, type safety ...

AceStack LLC

Java & Python Engineer

Sunrise, FL · On-site

Integrate LLMs with mcp servers, vector databases, and observability systems for adaptive agent behavior. Ensure reliability, performance, and maintainability through rigorous testing, type safety ...

AceStack LLC

Java & Python Engineer

Fort Lauderdale, FL · On-site

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

Diverse Lynx

Java-Python-Senior Engineer

Sunrise, FL · On-site

Integrate LLMs with mcp servers, vector databases, and observability systems for adaptive agent behavior. Ensure reliability, performance, and maintainability through rigorous testing, type safety ...

Insight Global

AI Engineer

Fort Lauderdale, FL · Remote

$65 - $75/hr

Create Retrieval-Augmented Generation (RAG) solutions utilizing enterprise knowledge bases and vector databases. * Design APIs and integrations connecting AI solutions to enterprise systems. Agentic ...

Diverse Lynx

Java and Python Developer

Sunrise, FL · On-site

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

Diverse Lynx

Junior Developer (Java+ Python)

Sunrise, FL · On-site

$80K - $90K/yr

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

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All JobsVector Databases JobsVector Databases Jobs in Miami, FL

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 Miami, FL? For Vector Databases jobs in Miami, FL, the most frequently searched job titles are:
What job categories do people searching Vector Databases jobs in Miami, FL look for? The top searched job categories for Vector Databases jobs in Miami, FL are:
What cities near Miami, FL are hiring for Vector Databases jobs? Cities near Miami, FL with the most Vector Databases job openings:
Vector Databases jobs near you
Gen AI Engineer - Sunrise, FL - Contract Opportunity

Gen AI Engineer - Sunrise, FL - Contract Opportunity

Zodiac Solutions

Sunrise, FL • On-site

Contractor

Posted 12 days ago

Job description

Role: Gen AI Engineer

Location: Sunrise, FL (Onsite/Hybrid as per client requirement)
Duration: Long-Term Contract
Required Skills: Python, GenAI, LLM, LangChain, LangGraph, RAG.


Experience: 6+ Years

Job Description:

  • Design and develop AI-powered applications using Python and modern GenAI frameworks.
  • Build and optimize LLM-based solutions using LangChain and LangGraph.
  • Develop RAG pipelines by integrating vector databases and enterprise knowledge sources.
  • Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases.
  • Knowledge of AI model integration using APIs such as OpenAI, Anthropic, or similar platforms.
  • Experience developing and deploying AI applications in cloud environments (AWS, Azure, or GCP).
  • Strong understanding of REST APIs, microservices, and scalable application architecture.
  • Familiarity with Git, CI/CD pipelines, and Agile methodologies.