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Pinecone Vector Databases Jobs in California (NOW HIRING)

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

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 ...

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 ...

Jobzhr

AI Agent Engineer

Cupertino, CA · On-site

$180 - $240/hr

Experience with vector databases (Pinecone, FAISS, Milvus, etc.) * Knowledge of evaluation methods for generative AI systems * Experience deploying AI systems on cloud platforms (AWS, GCP, Azure)

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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.

Python Engineer C2C requirements at San Jose, CA

Tech Mirrors

San Jose, CA • On-site

$100 - $140/hr

Other

Posted 10 days ago

Job description

Job Role Python Engineer

Location: San Jose, CA (Onsite Role)

Mandatory Skills
  • Language: Expert-level proficiency in Python (3.10+ preferred)
  • Frameworks: Deep experience with FastAPI, Django
  • AI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows
  • Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate)
  • Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues
Job Description Role Overview

We are looking for a Python Developer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex architectural puzzles and want to work at the intersection of traditional backend engineering and AI

Core Responsibilities
  • Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests
  • Agent Logic Integration: Architect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services
  • Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints
  • Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways or Service Meshes
Required Technical Skills
  • Language: Expert-level proficiency in Python (3.10+ preferred)
  • Frameworks: Deep experience with FastAPI, Django
  • AI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows
  • Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate)
  • Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues
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