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Pinecone Vector Databases Jobs in Ohio (NOW HIRING)

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

$140K - $220K/yr

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 · On-site +1

$140K - $220K/yr

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

$140K - $220K/yr

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

$140K - $220K/yr

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

VDart

Senior AI / ML Engineer

Mayfield Village, OH

$107K - $146K/yr

Spark/Databricks or equivalent; batch and streaming (e.g., Kafka). • Storage: relational and NoSQL; data lakes; vector databases (e.g., FAISS, Pinecone, Weaviate). • CI/CD (e.g., GitHub Actions ...

A-TEK Inc.

Federal AI Solutions Engineer

Continental, OH · On-site

$135K - $150K/yr

Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS) * Ability to design and debug distributed cloud systems and AI-enabled applications. * Strong communication skills: able to ...

Further

Senior AI Engineer

Cleveland, OH · On-site +1

$101K - $139K/yr

Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms. * Strong understanding of LLMOps principles, including model registry, versioning, and serving ...

GARGI TECHNOLOGIES INC

AI / GenAI Engineer

Ohio City, OH

$97K - $131K/yr

... with vector databases (Pinecone, Weaviate, Chroma, FAISS, Milvus) and orchestration of multi-agent and tool-using systems. 4. Strong backend development experience using FastAPI / Django REST ...

American Financial

AI Platform Engineer

Cincinnati, OH · Hybrid

Practical experience building RAG systems end-to-end: embeddings, vector databases (e.g., pgvector, Pinecone, Weaviate, Azure AI Search), retrieval tuning, and evaluation. * Working knowledge of MCP ...

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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 Ohio? For Pinecone Vector Databases jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Ohio look for? The top searched job categories for Pinecone Vector Databases jobs in Ohio are:
What cities in Ohio are hiring for Pinecone Vector Databases jobs? Cities in Ohio with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Dayton, OH • Remote

$140K - $220K/yr

Full-time

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

Job description

Frontier Technology Inc. (FTI) is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

For this role, the compensation range is $140k-$220k.

*Note: Starting pay will be based on a number of factors and commensurate with the candidate’s residence location, qualifications & experience.

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