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Pinecone Jobs (NOW HIRING)

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Develop and optimize RAG pipelines using vector databases (FAISS, Pinecone, Chroma) * Deploy models via APIs, microservices, Docker, and cloud platforms (AWS / GCP / Azure) * Implement CI/CD ...

GenAI Vector DB Engineer

$117K - $140K/yr

The ideal candidate will have expertise in designing, implementing, and optimizing vector databases, with a strong focus on utilizing ChoromDB/Pinecone for vector applications. The role involves ...

Sr Python Developer

Tampa, FL · On-site

$114K - $154K/yr

Integrate with external data sources (databases, APIs, vector databases like Pinecone, Weaviate, or FAISS) for context-rich AI solutions. * Collaborate with data scientists, ML engineers, and product ...

Experience with vector DBs (Pinecone, Milvus, Weaviate, FAISS) and semantic search pipelines. Cloud AI expertise (Azure AI Studio, AWS Bedrock, Vertex AI). Familiarity with MLOps / LLMOps: model ...

Gen AI Developer / Sr.

Irving, TX · On-site

$116K - $157K/yr

Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG). Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and containerization (Docker ...

Lead AI Engineer

Coppell, TX · On-site

$94K - $124K/yr

... Pinecone. • Implement eventing patterns using Kafka or Pub/Sub. • Utilize observability stacks including OpenTelemetry, Prometheus/Grafana, and Elk/Cloud Logging. • Employ infrastructure-as ...

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

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

Be Seen First

Design and optimize the storage of embeddings in Vector Databases (e.g., Pinecone, ChromaDB, Vertex AI Search) and Graph Databases (e.g., FalkorDB, Neo4j) to enable multi-step agentic reasoning ...

New

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

Experience with RAG frameworks and vector databases (Pinecone, FAISS, OpenSearch) * Knowledge of AWS services (Lambda, S3, API Gateway, IAM) Preferred: * Retail domain experience * LangChain or ...

Python Developer

Dallas, TX · On-site

$49.75 - $68.50/hr

... Pinecone * Portfolio of LLM applications and sample projects * 2+ years of NLP experience using tools such as NLTK, SpaCy, and Beautiful Soup * 1+ years of LLM experience building RAG systems at ...

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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 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 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.

More about Pinecone jobs
What cities are hiring for Pinecone jobs? Cities with the most Pinecone job openings:
What are the most commonly searched types of Pinecone jobs? The most popular types of Pinecone jobs are:
What states have the most Pinecone jobs? States with the most job openings for Pinecone jobs include:

Full-time

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


Job description

Vector Application Developer
Remote
Fulltime
Candidates may need to travel occasionally at client site.
Responsibilities:
The ideal candidate will have expertise in designing, implementing, and optimizing vector databases, with a strong focus on utilizing ChoromDB/Pinecone for vector applications. The role involves contributing to the development and maintenance of our data infrastructure, ensuring efficient handling of complex relationships and vectors.
  • Design and implement vector databases to efficiently store and retrieve high-dimensional vectors.
  • Optimize database queries, indexing strategies for vector operations.
  • Architect and performance tune vector pipeline for embedding and text similarity search
  • Identify and resolve performance bottlenecks to ensure efficient data retrieval.
  • Collaborate with application developers to integrate vector databases and knowledge graphs into various software solutions.
  • Provide support for query optimization and data modeling for application-specific requirements.
  • Implement and maintain data security measures for vector databases.
  • Ensure compliance with relevant data protection regulations and industry standards.
  • Work closely with cross-functional teams, including data scientists, software engineers, and product managers.
  • Communicate technical concepts and solutions effectively to both technical and non-technical stakeholders.

Technical skills:
  • Knowledge of distributed database systems.
  • Familiarity with machine learning and AI concepts related to vector data.
  • Experience with cloud-based database solutions.
  • Proven experience in designing and implementing vector databases, with a focus on ChromaDB/Pinecone etc for vector applications.
  • Strong proficiency in embeddings, vectorization, vector stores, database optimization, performance tuning, and relevant query languages.
  • Familiarity with embedding, retrieval algorithms, agents, data modeling for vector development graphs.
  • Experience with LLM and other related frameworks like Langchain, LLama
  • Experience with relevant programming languages, such as Python, Java, or Scala.
  • Excellent problem-solving skills and the ability to work in a collaborative team environment.

Soft skills:
  • Strong work ethic and desire to produce quality results
  • Consistently and proactively communicates (verbally/written) to stakeholders (progress/roadblocks/etc.)
  • Continuous Improvement mindset and approach to work product
  • Ability to take complex subjects and simplify it to less technical individuals
  • Provides clear documentation of processes, workflows, recommendations, etc.
  • High level of critical thinking capabilities
  • Organized and has the ability to manage work effectively, escalating issues as appropriate
  • Takes initiative & is a self-starter
  • Displays ownership of their work (quality, timeliness)
  • Seeks to become an expert in their field and shares their expertise through recommendations, proactive communications/actions and peer sharing/coaching where relevant
  • Should be able to communicate with stakeholders directly and independently
  • Should have good problem solving skills

Candidate Profile:
  • Bachelor's/Master's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas; candidates with BA/BS degrees in the same fields from the top tier academic institutions are also welcome to apply
  • 8+ years of experience working with data engineering with atleast 2-3 years of experience working on vector databases.
  • Strong experience with vector databases including ChromaDB, Pinecone and corresponding implementations over cloud platforms (AWS, Azure etc.)
  • Outstanding written and verbal communication skills
  • Superior analytical and problem solving skills
  • Experience in working in dual shore engagement is preferred
  • Must have experience in managing clients directly
  • Strong record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work
  • Able to work in fast pace continuously evolving environment and ready to take up uphill challenges
  • Is able to understand cross cultural differences and can work with clients across the globe