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Vector Databases Jobs in Bridgewater, MA (NOW HIRING)

Saviance

Senior Data / RAG Engineer

Boston, MA · On-site

$115K - $156K/yr

Design and implement RAG Vector Databases (e.g., OpenSearch, Pinecone) using archival data from S3 / Glacier and overall data management via MS SQL Server . * Modernize existing data ingestion ...

Globalchannelmanagement

Remote AI Architect

Boston, MA · Remote

$90 - $92/hr

Experience with MLOps/LLMOps ecosystems, including tools such as MLflow, Kubernetes, LangChain, vector databases, and feature stores. * Strong hands on experience with ML frameworks, LLM platforms ...

JLL

Lead AI Engineer

Boston, MA

$111K - $146K/yr

Experience working with vector databases, knowledge graphs, and RAG pipeline development * Advising on best practices for AI agent development and enterprise AI integration processes * Experience in ...

Saviance

Data Engineer (Agentic AI)

Boston, MA · On-site

$124K - $149K/yr

Integrate enterprise data sources with AI agents, APIs, vector databases, and semantic search systems. * Implement data quality, governance, monitoring, and observability practices across the data ...

JLL

Senior Software Engineer, AI Platforms

Boston, MA

$133K - $175K/yr

Experience with vector databases, information retrieval systems, and optimizing search performance (highly preferred). * Familiarity with containerization (Docker, Kubernetes) and infrastructure-as ...

SevenAI

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

Tool fluency - comfortable with RAG, vector databases (e.g., Pinecone/Weaviate), workflow frameworks (LangChain, Dust), and related tooling. * Architectural thinker - you can diagram end-to-end ...

The Mutual Group

Lead AI Engineer - AWS Platform

Boston, MA · On-site +1

$130K - $190K/yr

Build RAG pipelines using vector databases and enterprise data sources * Build machine learning models that automate their training, validation, monitoring, and retraining * Develop APIs and services ...

FocusKPI Inc.

Junior AI/ML Engineer (Remote)

Boston, MA · Remote

Knowledge of vector databases or embeddings * Familiarity with AWS, GCP, or Azure * Prior internship or project experience building AI/ML applications How to Apply Please submit the following to danz ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$30 - $35/hr

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$35 - $45/hr

Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) * Experience in RAG (Retrieval-Augmented Generation) implementations. * Knowledge of MLOps tools and CI/CD pipelines. * Experience with ...

The Hollister Group

AI Developer

Boston, MA · On-site

$70 - $110/hr

Build retrieval-augmented generation (RAG) systems using Azure AI Search, Amazon Kendra, or vector databases like Pinecone, Weaviate, or FAISS. * Deploy and manage models on Azure Machine Learning ...

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All JobsVector Databases JobsVector Databases Jobs in Bridgewater, MA

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 cities near Bridgewater, MA are hiring for Vector Databases jobs? Cities near Bridgewater, MA with the most Vector Databases job openings:
Vector Databases jobs near you
Senior Data / RAG Engineer

Senior Data / RAG Engineer

Saviance

Boston, MA • On-site

$115K - $156K/yr

Other

Posted 29 days ago

Job description

Senior Data / RAG Engineer
Location: Chennai / Hybrid
Employment Type: Full-time
Role Overview:
We're looking for a Senior Data Engineer with deep expertise in RAG (Retrieval-Augmented Generation) and Vector Database design to build and manage the knowledge backbone for AI compliance and insights. This role focuses on modernizing archival data ingestion and enabling real-time contextual retrieval for AI-driven systems.
Key Responsibilities:
  • Design and implement RAG Vector Databases (e.g., OpenSearch, Pinecone) using archival data from S3 / Glacier and overall data management via MS SQL Server.
  • Modernize existing data ingestion pipelines, replacing legacy OCR-based processes with scalable ETL/ELT frameworks.
  • Ensure data synchronization and consistency between RDS (MS SQL Server) and Vector DB for real-time AI context.
  • Collaborate with AI, backend, and infrastructure teams to optimize retrieval performance and model access.
  • Drive data integrity, schema evolution, and compliance readiness across systems.
Required Skills & Experience:
  • Proven expertise in data engineering pipelines (Kafka / MSK, ETL / ELT).
  • Hands-on experience with Vector Databases and RAG implementations (OpenSearch, Pinecone, FAISS, Chroma).
  • Strong proficiency in SQL, data modeling, and Python / C# / Go.
  • Experience with AWS data ecosystem (S3, RDS, Glue, Lambda and related technologies).
  • 8-10 years of experience in data engineering or AI data platforms.
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About Saviance

Sourced by ZipRecruiter

Saviance is a modern consulting firm providing a variety of professional services to its clients in the US. We bring twenty three years of experience to the table. Our consultants are qualified experts and extremely talented. We understand the business behind the technology, and work with many of the top Fortune 100 companies and provide innovative, scalable, robust and secure solutions. At the forefront of the Staffing and IT Solutions industry, Saviance is certified by NMSDC as a Tier 1, Minority Business Enterprise (MBE) . We are a self- certified Small Business and self- certified Woman Owned Business committed to maximizing global workforce solutions on behalf of our clients, empowering businesses and talent through applied human intelligence. We are a Diversity Supplier with global reach specializing in a business services blend of talent, technology, and a relentless commitment to customer success. It’s our diversity that’s acts as a core component of our culture, our approach to business, and the opportunities we provide to our clients and our employees.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

East Rutherford, NJ, US

Year founded

1999

Social media

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