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Pinecone Jobs (NOW HIRING)

VIS IT Solutions Inc

AI Architect

Miami, FL · On-site

... DBs (Pinecone, DB Vector) o LangChain / LlamaIndex or similar orchestration frameworks o Fine tuning & embeddings • Experience/familiarity with document chunking, knowledge graphs, and ...

Brillius

AI Architect

Miami, FL · On-site

... DBs (Pinecone, DB Vector) o LangChain / LlamaIndex or similar orchestration frameworks o Fine tuning & embeddings • Experience/familiarity with document chunking, knowledge graphs, and ...

Xoriant Corporation

Sr. Java Developer

Manhattan, NY

$63 - $80.50/hr

Exposure to: o Agentic AI / GenAI (LangChain, AutoGPT, CrewAI, Semantic Kernel) o LLMs (OpenAI, Azure OpenAI) o Vector DBs (Pinecone, FAISS, Chroma) _____ Nice to Have * Python, AWS/Azure/Google ...

Compunnel

Senior AI Engineer

Coppell, TX · On-site

$96K - $132K/yr

... and Pinecone. • Familiarity with Kafka or Pub/Sub eventing patterns. • Implement and maintain observability stacks: OpenTelemetry, Prometheus/Grafana, Elk/Cloud Logging. • Utilize ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). * Write clean, efficient Python code for data ingestion, feature ...

Palnar

ONLY W2 | AI Engineer@ Denver, Co

Denver, CO · On-site

Familiarity with Vector Databases (Pinecone, Weaviate, FAISS, Milvus, etc.). * Knowledge of ML pipelines, APIs, and prompt engineering. Excellent problem-solving, communication, and collaboration ...

Purple Drive Technologies

Sr. AI/ML Engineer

Jersey City, NJ · On-site

$109K - $149K/yr

Fine-tune and deploy LLMs integrated with vector databases (FAISS, Pinecone, ChromaDB). Detailed Description: • Experienced AI/ML Engineer with expertise in Machine Learning, Deep Learning, NLP ...

Waste Connections of Canada

$15.75 - $18.50/hr

PineCone Recycling has an immediate position available for a Yard Laborer at our location in Elkhart, Indiana . Responsibilities Include: * Maintaining the cleanliness of the site * Help maintain ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). * Write clean, efficient Python code for data ingestion, feature ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). * Write clean, efficient Python code for data ingestion, feature ...

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Pinecone information

What is a Pinecone job?

A Pinecone job typically refers to working with Pinecone, a vector database designed for machine learning and AI applications. Roles can range from engineering positions that focus on optimizing search and retrieval to data science roles that work with embeddings. Pinecone jobs often require knowledge of machine learning, data indexing, and scalable infrastructure.

What are the typical responsibilities and challenges for an engineer working with Pinecone vector databases?

Engineers working with Pinecone typically focus on building, maintaining, and scaling vector search solutions that power features like semantic search and recommendations. Daily tasks often include integrating Pinecone with other data systems, optimizing indexing and query performance, and ensuring high availability. Common challenges involve efficiently handling large-scale data, managing latency requirements, and troubleshooting distributed system issues. Collaboration with data scientists and backend engineers is frequent to ensure seamless model integration and real-time data flows.

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

To thrive as a Pinecone Engineer, you need a solid background in computer science, experience with vector databases, and proficiency in programming languages such as Python or Java. Familiarity with Pinecone's vector database platform, cloud infrastructure (like AWS, GCP, or Azure), and API integration is typically required. Strong problem-solving skills, collaboration, and effective communication set standout engineers apart in this role. These competencies are crucial for building scalable, high-performance search applications and ensuring seamless integration with organizational data systems.

What kind of company is Pinecone?

Pinecone is a technology company that provides a managed vector database service designed for machine learning and AI applications. It focuses on enabling fast similarity search and scalable data management for developers working with high-dimensional data. Employees working there often need skills in software engineering, data structures, and cloud infrastructure.

What are Pinecone engineers?

Pinecone engineers are professionals who work with Pinecone, a vector database service designed for building and deploying machine learning applications that require similarity search and retrieval of high-dimensional data. Their role often involves integrating Pinecone into various technology stacks, optimizing data pipelines, and ensuring efficient large-scale vector search for features like recommendation systems, semantic search, or AI-powered applications. They typically have expertise in Python, APIs, machine learning concepts, and cloud infrastructure. Pinecone engineers help organizations manage and scale their AI search capabilities effectively.

What are the career opportunities for Python?

For Python developers, career opportunities include roles such as software engineer, data analyst, machine learning engineer, and backend developer. These positions often require proficiency in Python programming, knowledge of frameworks like Django or Flask, and familiarity with tools such as Git and Docker.

Is pinecone high availability?

Pinecone, as a managed vector database service, is designed for high availability with features like data replication and fault tolerance to ensure minimal downtime. It typically operates in cloud environments that support redundancy and automatic failover, making it suitable for production workloads requiring reliable access. Job roles involving Pinecone may require understanding of distributed systems and cloud infrastructure to maintain high availability.

What is the difference between Pinecone vs Data Scientist?

AspectPineconeData Scientist
Required CredentialsTechnical skills in databases, APIs, and cloud platformsDegree in Computer Science, Statistics, or related fields; often includes certifications
Work EnvironmentTech companies, startups, cloud service providersResearch labs, corporate teams, consulting firms
Industry UsageData management, vector similarity search, AI applicationsData analysis, predictive modeling, machine learning
Common Search/ComparisonYesYes

While Pinecone specializes in vector database management and similarity search technology, Data Scientists focus on analyzing data, building models, and deriving insights. Both roles often collaborate in AI projects, but their core skills and tools differ significantly.

Is pinecone free or paid?

Pinecone offers both free and paid plans for its vector database service. The free tier provides limited usage suitable for testing and small projects, while paid plans include additional features and higher usage limits for production environments.
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Pinecone jobs near you

AI Architect

VIS IT Solutions Inc

Miami, FL • On-site

Contractor

Posted 28 days ago

Job description

Hi,

Please find the job description below

Role: AI Architect – Onsite

Location: Miami, FL

Duration: 6 months

GBaMS ReqID: 10641871

JD:

• 10–15 years in AI, ML, or enterprise architecture roles.

• Proven track record architecting RAG systems, vector search, and LLM-based knowledge platforms.

• Strong hands-on experience with:

o Python

o Cloud ML platforms-Azure

o Vector DBs (Pinecone, DB Vector)

o LangChain / LlamaIndex or similar orchestration frameworks o Fine tuning & embeddings • Experience/familiarity with document chunking, knowledge graphs, and vectorization • Expertise in document AI, NLP, and unstructured data processing.

• Strong architectural skills across:

o Data pipelines

o APIs and event-driven systems

o Containerization (Docker/K8s)

o Security-by-design

• Experience in financial services, preferably in commercial real estate credit, servicing, or asset management.