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Pinecone Vector Databases Jobs in Washington, DC

Experience building RAG solutions and working with vector databases (e.g., Pinecone, FAISS) * Knowledge of prompt engineering and content filtering techniques * Familiarity with frameworks such as ...

Experience building RAG solutions and working with vector databases (e.g., Pinecone, FAISS) * Knowledge of prompt engineering and content filtering techniques * Familiarity with frameworks such as ...

Experience building RAG solutions and working with vector databases (e.g., Pinecone, FAISS) * Knowledge of prompt engineering and content filtering techniques * Familiarity with frameworks such as ...

Experience building RAG solutions and working with vector databases (e.g., Pinecone, FAISS) * Knowledge of prompt engineering and content filtering techniques * Familiarity with frameworks such as ...

Lead Data Architect

Herndon, VA · On-site

$160 - $190/hr

Experience integrating Databricks with vector databases (Pinecone, neo4j) and retrieval frameworks (LangChain, LlamaIndex). * Familiarity with AWS Bedrock or other managed LLM services. * Experience ...

Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and vector databases (FAISS, Milvus, Pinecone, or similar). * Advanced knowledge of cloud platforms (AWS ...

Senior LLMOps Engineer

Mclean, VA · On-site

$145K - $185K/yr

Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and vector databases (FAISS, Milvus, Pinecone, or similar). * Advanced knowledge of cloud platforms (AWS ...

Senior LLMOps Engineer

Mclean, VA · On-site

$145K - $185K/yr

Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and vector databases (FAISS, Milvus, Pinecone, or similar). * Advanced knowledge of cloud platforms (AWS ...

Showing results 21-40

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 Washington, DC?

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

What job categories do people searching Pinecone Vector Databases jobs in Washington, DC look for?

The top searched job categories for Pinecone Vector Databases jobs in Washington, DC are:

Infographic showing various Pinecone Vector Databases job openings in Washington, DC as of June 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Machine Learning Engineer with Security Clearance

Stillwater Human Capital

Chantilly, VA • On-site

$179K - $236K/yr

Other

Re-posted 4 days ago


Job description

Machine Learning Engineer Location: Chantilly, VA Clearance: Active TS/SCI w/Polygraph The Opportunity Stillwater is searching for a Software Developer with expertise in artificial intelligence to join its dynamic team. This position centers on developing and implementing AI solutions to strengthen enterprise-level IT operations. The Machine Learning Engineer will collaborate closely with cross-functional teams to design, develop, and deploy AI-driven applications that enhance efficiency, automate processes, and deliver valuable insights. Responsibilities * Develop and maintain machine learning pipelines and applications using Python and contemporary machine learning frameworks. * Implement and optimize algorithms for integrating and deploying large language models (LLMs). * Build RESTful APIs and microservices to serve machine learning models in production environments. * Write clean, maintainable, and well-documented code, adhering to object-oriented programming principles. * Collaborate with cross-functional teams to understand requirements and convert them into technical solutions. * Manage training data, model artifacts, and application state using SQL, NoSQL, and vector databases. * Containerize machine learning applications with Docker to ensure consistent deployment across environments. * Use Git for version control and participate in code reviews to maintain code quality. * Conduct testing and debugging of machine learning applications to ensure reliability and accuracy. * Support the deployment and monitoring of AI and machine learning models in cloud environments. * Stay up to date with emerging trends in machine learning, LLMs, and AI engineering best practices. Qualifications Required * Active TS/SCI clearance with Poly. * Bachelor's degree in computer science, software engineering, data science, or a related technical field, plus five years of professional experience in software development or machine learning engineering. * Strong proficiency in Python programming, with a thorough understanding of object-oriented programming concepts, design patterns, data structures, and algorithms. * Experience with development tools and practices, including Git version control, Docker containerization, and database management (SQL and/or NoSQL). * Knowledge of large language model technologies, including familiarity with orchestration frameworks such as LangChain and LangGraph. * Understanding of retrieval-augmented generation (RAG) architectures and vector databases (including ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems. * Strong problem-solving skills, attention to detail, excellent communication abilities, and eagerness to learn within a collaborative team environment. Desired * Master's degree in computer science or a related field. * Experience with cloud platforms such as AWS, Azure, or Google Cloud, and knowledge of MLOps practices for machine learning model deployment and monitoring. * Experience with container orchestration and DevOps, including Kubernetes, Rancher, CI/CD pipelines, and infrastructure automation tools like Ansible. * Familiarity with enterprise platforms such as ServiceNow, SAP, Tableau, or Splunk. * Contributions to open-source machine learning projects and familiarity with Agile development methodologies. Salary Range: $179,000 - $236,200 The above salary range represents a general guideline. Stillwater considers a number of factors when determining base salary offers, such as the scope and responsibilities of the position and the candidate's experience, education, skills, and current market conditions. Depending on the position, employees may be eligible for overtime and/or discretionary bonuses in addition to base pay. Stillwater is an Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, or any other protected class. If you need assistance with the application process due to a disability, please contact us at 571-525 2482