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Pinecone Vector Databases Jobs in California (NOW HIRING)

Robustware

AI/ML Engineer

Cupertino, CA · On-site

Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies * Hands-on experience with Kubernetes, Docker, and scalable API deployment * Ability to ...

Tanisha Systems, Inc.

AI/ML Engineer

Cupertino, CA · On-site

Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies * Hands-on experience with Kubernetes, Docker, and scalable API deployment ...

Innowhyte Inc

Build and implement RAG pipelines with vector databases (e.g., Pinecone, FAISS). Develop Generative AI solutions, including chatbots, summarization, and content creation tools. Preprocess, clean, and ...

CYNET SYSTEMS

ML Engineer

Woodland Hills, CA · On-site

$56 - $61/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience working with Vector Databases and/or MongoDB. Responsibilities: Design and develop ... Vector DBs (Pinecone, Chroma, Weaviate, Milvus, FAISS). Hugging Face. MLflow. FastAPI. Docker ...

CYNET SYSTEMS

ML Engineer

Woodland Hills, CA · On-site

$56 - $61/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience working with Vector Databases and/or MongoDB. Responsibilities: * Design and develop ... Vector DBs (Pinecone, Chroma, Weaviate, Milvus, FAISS). * Hugging Face. * MLflow. * FastAPI.

Inficare Technologies

AI Architect

San Diego, CA · On-site

$67 - $88/hr

Vector Databases: Pinecone, Weaviate, Milvus, Chroma, Azure AI Search * Frameworks: LangChain, LangGraph, LlamaIndex * Azure: Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, AKS ...

New

Apple, Inc.

AI Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... with vector databases (Pinecone, Weaviate, Chroma), embedding generation pipelines, document stores (MongoDB or similar) and their integration patterns Understanding of RAG, MCP architectures ...

Apple

AI Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... with vector databases (Pinecone, Weaviate, Chroma), embedding generation pipelines, document stores (MongoDB or similar) and their integration patterns Understanding of RAG, MCP architectures ...

Siri InfoSolutions Inc

AI/ML Engineer

Santa Clara, CA · On-site

Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows ... Expertise in Python, vector DBs (Elastic, Milvus, Pinecone, etc.), embeddings, chunking. Experience ...

Kai Cyber, Inc.

Senior Data Engineer, AI Platform

San Jose, CA · On-site

$124K - $168K/yr

Data preparation for LLM and GenAI systems Vector Databases & Retrieval Systems * Milvus, Pinecone, Databricks Vector Search, FAISS * ANN algorithms (HNSW, IVF, PQ) * Hybrid retrieval (BM25 + vector ...

Ingram Micro, Inc.

Software Engineer - AI

Irvine, CA · On-site

$110 - $130/hr

PostgreSQL, SQL databases, NoSQL databases, Vector Databases (pgvector, Pinecone, Weaviate, ChromaDB, etc.). * Exposure to one or more Cloud Platforms, such as: Google Cloud Platform (GCP), Amazon ...

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Pinecone Vector Databases information

What is a Pinecone vector database?

A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.

What are the key skills and qualifications needed to thrive as a Pinecone vector database engineer, and why are they important?

To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.

What are some common challenges faced by engineers working with Pinecone vector databases, and how can they be addressed?

Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.

What is the difference between Pinecone Vector Databases vs Data Engineers?

AspectPinecone Vector DatabasesData Engineers
Primary RoleManaging and deploying vector database solutions for AI/ML applicationsDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsKnowledge of vector databases, cloud platforms, programming (Python, SQL)Data modeling, ETL processes, cloud services, programming (Python, Java)
Work EnvironmentTech companies, AI startups, cloud providersData-driven organizations, tech firms, finance, healthcare

While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.

What are popular job titles related to Pinecone Vector Databases jobs in California?

For Pinecone Vector Databases jobs in California, the most frequently searched job titles are:

What job categories do people searching Pinecone Vector Databases jobs in California look for?

The top searched job categories for Pinecone Vector Databases jobs in California are:

What cities in California are hiring for Pinecone Vector Databases jobs?

Cities in California with the most Pinecone Vector Databases job openings:

Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in California as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 81% Physical, 6% Hybrid, and 13% Remote job distribution.

AI/ML Engineer

Robustware

Cupertino, CA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

  • Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows
  • Design agentic AI systems — including tool calling, orchestration, reasoning loops, and workflow automation
  • Develop Applied AI solutions that integrate with customer backend systems, APIs, and data sources
  • Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure
  • Work directly with customers to deliver high-quality technical implementations, demos, and documentation


Preferred SKILLS:

  • Strong experience with LLMs and agent frameworks such as LangChain, LlamaIndex, or custom-built solutions
  • Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies
  • Hands-on experience with Kubernetes, Docker, and scalable API deployment
  • Ability to understand customer workflows and translate them into actionable technical solutions

Apply