1 to 25 of 49 Permanent Pinecone Jobs

QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming & APIs: Expert-level Python and demonstrable experience building production services with FastAPI. Cloud Platform: Mastery of GCP, particularly Vertex AI, Google Kubernetes Engine (GKE More ❯

QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming & APIs: Expert-level Python and demonstrable experience building production services with FastAPI. Cloud Platform: Mastery of GCP, particularly Vertex AI, Google Kubernetes Engine (GKE More ❯

such as LangChain, LangGraph, CrewAI, PydanticAI, CoPilotKit, A2A, MCP. Integrate agentic AI systems through tools such as retrieval-augmented generation (RAG), memory/context management, and vector databases (e.g., Pinecone, Weaviate, FAISS). Experience working with end users to streamline workflows and produce applied solutions. Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation More ❯

Languages: Python (primary), JavaScript/TypeScript (optional) Orchestration/Workflow: LangGraph, Haystack, Hugging Face, RAG pipelines MLOps/Deployment: Docker, Kubernetes, CI/CD, REST APIs Other: Vector Databases (Pinecone, FAISS, Chroma), Prompt Engineering, RAG systems More ❯

directly in AI/ML development Core AI/ML Competencies: Expertise with large language models (LLMs), retrieval-augmented generation (RAG), and embedding models Experience with vector databases (e.g., Pinecone, Quadrant, Chroma) and indexing & similarity search (e.g., FAISS, HNSW, ScaNN, Annoy) Proficiency in hybrid search methods (semantic + keyword search, e.g., BM25 + ANN) and metadata filtering/hybrid retrieval More ❯

OpenAI or Anthropic Experience with basic prompt engineering concepts and use of LLM SDKs or frameworks including LangChain or LlamaIndex Experience with a vector database or search framework including Pinecone, Weaviate, or FAISS Experience developing backend services and building or consuming RESTful APIs Ability to follow code review practices, document work, and maintain clean and reusable code Ability to obtain More ❯

RAG) . Proficiency in Python, JavaScript/TypeScript, or similar programming languages . Experience with cloud platforms (AWS, Azure, GCP) and AI/ML deployments. Familiarity with Vector Databases (Pinecone, Weaviate, FAISS, Milvus, etc.) . Knowledge of ML pipelines, APIs, and prompt engineering . Excellent problem-solving, communication, and collaboration skills. Preferred Qualifications Healthcare industry background or prior work on More ❯

RAG) . Proficiency in Python, JavaScript/TypeScript, or similar programming languages . Experience with cloud platforms (AWS, Azure, GCP) and AI/ML deployments. Familiarity with Vector Databases (Pinecone, Weaviate, FAISS, Milvus, etc.) . Knowledge of ML pipelines, APIs, and prompt engineering . Excellent problem-solving, communication, and collaboration skills. Preferred Qualifications Healthcare industry background or prior work on More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

to production-scale AI or ML-enabled applications Experience integrating LLMs or multimodal models into user-facing applications or workflow tools Experience with RAG systems using vector databases, including Pinecone, Weaviate, ChromaDB, or FAISS, and embedding models Experience with backend engineering in Python Experience building or supporting AI agents, including using frameworks such as LangChain, LlamaIndex, or CrewAI Knowledge of More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

with relevant technologies such as OpenAI, LangChain/LangGraph, LlamaIndex Experience with Hugging Face and LoRA/QLoRA for fine-tuning Experience with RAG & Vector DBs eg. FAISS, Weaviate, Pinecone Any experience of MLOps with MLFlow, AWS (SageMaker), CI/CD (GitHub Actions) or similar would be a benefit to an application The employer is well known not only for More ❯

experience building retrieval-augmented AI search solutions. LLM Fine-Tuning: Experience fine-tuning models for domain-specific performance and optimizing inference speed. Vector Search: Knowledge of DataStax Vector Search, Pinecone, FAISS, or Weaviate. Deployment: Familiarity with Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Jenkins, or similar). Security & Authentication: Strong understanding of OAuth2, JWT, and API security best More ❯

and Microservices architecture. Experience with LLMs and related technologies. Hands-on experience integrating with OpenAI (RAG) services (e.g., GPT models) and Azure AI services. Familiarity with vector databases (e.g., Pinecone, Weaviate, Chroma Experience with version control (Git) and testing. Excellent problem-solving and communication skills. Preferred Qualifications: Experience with cloud platforms (e.g., Azure, AWS, GCP Knowledge of machine learning algorithms More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯