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Pinecone Vector Databases Jobs in Michigan (NOW HIRING)

Orbotech

AI Software Engineer|Manufacturing

Ann Arbor, MI · On-site

$111K - $188K/yr

Knowledge of retrieval-augmented generation (RAG) and vector databases (e.g., Pinecone, FAISS, Azure Cognitive Search) * Vector database (Milvus) for semantic search, along with a knowledge graph ...

Kla

AI Software Engineer|Manufacturing

Ann Arbor, MI · On-site

$111K - $188K/yr

Knowledge of retrieval-augmented generation (RAG) and vector databases (e.g., Pinecone, FAISS, Azure Cognitive Search) * Vector database (Milvus) for semantic search, along with a knowledge graph ...

X by 2

Technical Lead (Applied AI)

Detroit, MI

Agentic SQL retrieval, MCP integration, agentic tool use, as well as vector databases & RAG techniques implementing retrieval-augmented generation patterns using vector stores (e.g., Pinecone ...

Deloitte

Cyber - SecOps - Consultant

Detroit, MI

Qualifications Required: * 2+ years of analytics consulting or industry experience * 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone ...

All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Michigan

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.

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Pinecone Vector Databases jobs near you

AI/ML Solutions Architect

Up2date Technologies

Grand Rapids, MI • On-site

Other

Posted 3 days ago

New

Job description

Role: AI/ML Solutions Architect
Location: Grand Rapids, MI (Onsite)
Job Type: Full-Time

Job Description:
We are seeking an experienced AI/ML Solutions Architect to lead the design and implementation of enterprise AI solutions. The ideal candidate will have strong expertise in Generative AI, LLMs, RAG, AI architecture, MLOps, and cloud AI platforms with a proven track record of building scalable AI systems.

Required Skills:
Generative AI (GenAI)
Large Language Models (LLMs – GPT, Llama, Claude)
Retrieval-Augmented Generation (RAG)
AI/ML Solution Architecture
Python
TensorFlow / PyTorch / Scikit-learn
MLOps (MLflow, Kubeflow, SageMaker, Vertex AI)
AWS, Azure & Google Cloud Platform AI Services
Data Engineering (ETL, Data Lakes, Streaming)
Vector Databases (Pinecone, Weaviate, Chroma, FAISS)
APIs, Microservices & Distributed Systems
CI/CD & DevOps for ML
Code Generation Tools (GitHub Copilot, Cursor, Claude Code)

Responsibilities:
Design and implement enterprise AI/ML architectures.
Build scalable GenAI and RAG-based solutions.
Develop AI systems using LLMs and modern ML frameworks.
Establish MLOps practices for deployment, monitoring, and model lifecycle management.
Design data pipelines and AI infrastructure on cloud platforms.
Collaborate with cross-functional teams to deliver AI-driven solutions.
Evaluate emerging AI technologies and define architecture best practices.

Qualifications:
10+ years of software engineering and/or data science experience.
3–5+ years of AI/ML architecture experience.
Strong expertise in GenAI, LLMs, RAG, NLP, and deep learning.
Hands-on experience with cloud AI services and scalable AI platforms.
Excellent communication and solution architecture skills.

Apply