26 to 50 of 54 Pinecone Jobs

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 ❯

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 ❯

Architect and implement LLM-powered workflows using OpenAI, Anthropic, and other APIs (e.g. summarisation, analysis, benchmarking). Develop retrieval-augmented generation (RAG) pipelines connecting structured/unstructured data (Supabase, Pinecone, Chroma). Design and maintain evaluation systems — to assess LLM output quality, bias, and reliability. Build a reinforcement learning feedback loop , where user interactions and outcome data improve future model More ❯

Experience building with generative AI applications in production environments. Expertise with microservices architecture and RESTful APIs. Solid understanding of database technologies such as PostgreSQL and vector databases as Elastic, Pinecone, Weaviate, or similar. Familiarity with cloud platforms (AWS, GCP, etc.) and containerized environments (Docker, Kubernetes). Familiarity with MCP, devtools, AI agents, or contributed to open source You are committed More ❯

influenced ARR aligned with GTM metrics. Required Qualifications 5+ years in AI/ML engineering, applied AI, or solutions engineering roles. Proven experience with: RAG pipelines (LangChain, LlamaIndex, Weaviate, Pinecone, Milvus, etc.) Fine-tuning LLMs (LoRA, PEFT, instruction-tuning, domain adaptation) Deploying inference endpoints at scale (Triton, HuggingFace Inference, Ray Serve, Kubernetes) Strong coding skills in Python (and ideally one More ❯

vLLM, TGI, llama.cpp) Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.) Experience with both SQL and NoSQL databases at scale Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector) Experience with computer vision libraries (OpenCV, PIL) and video processing Understanding of MLOps practices and model lifecycle management Preferred Qualifications Experience with military/defense AI applications Knowledge More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

Practical experience with memory frameworks like Mem0 or Letta. Understanding and production experience with traditional RAG and agentic RAG architectures. Strong grasp of embedding systems and vector databases (e.g., Pinecone, Weaviate, FAISS). Production experience with LiveKit or similar audio/video platforms. What You’ll Be Doing: Building and deploying scalable AI features, agents, and services powered by LLMs. More ❯

chaining, and optimization for LLMs. Hands-on expertise with Amazon Bedrock, including model integration, Guardrails, and KnowledgeBases. Proficient in Python, API integration, and working with vector databases (e.g., FAISS, Pinecone). Solid understanding of LLM behavior, RAG architecture, and deploying AI solutions on AWS cloud. More ❯

in data engineering, ML engineering, or similar technical roles Strong Python skills and comfort working across complex ingestion workflows Experience managing NoSQL and vector databases at scale (MongoDB, Weaviate, Pinecone, etc.) Solid understanding of modern data pipeline tools (Airflow, Prefect, Dagster) Practical experience with LLM development, embeddings, and RAG architectures Familiarity with distributed systems and cloud platforms (AWS, GCP, or More ❯

in data engineering, ML engineering, or similar technical roles Strong Python skills and comfort working across complex ingestion workflows Experience managing NoSQL and vector databases at scale (MongoDB, Weaviate, Pinecone, etc.) Solid understanding of modern data pipeline tools (Airflow, Prefect, Dagster) Practical experience with LLM development, embeddings, and RAG architectures Familiarity with distributed systems and cloud platforms (AWS, GCP, or More ❯

from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape the product roadmap. An environment … Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning, Vector Databases, Pinecone, Weaviate, Semantic Search, API Development, AI Deployment, Model Serving, AI Automation, Early Stage Startup, AI Startups, Tech Startup, Machine Intelligence, Applied AI, AI Applications, AI Innovation, AI Product Development, AI More ❯

end frameworks (e.g. React, Next.js, React Native) and back-end systems (e.g. Node.js, Python). AI integrations: Hands-on experience integrating AI tools and services (e.g. OpenAI, Anthropic, LangChain, Pinecone, speech/video APIs). Prototype mindset: You've built MVPs in fast-moving environments and are comfortable with ambiguity. Cloud/data experience: Familiar with AWS, GCP, or Firebase More ❯

standards, and accessibility (Section 508 compliance). Apply skills with Natural Language Processing (NLP), Large Language Models (LLMs) like Llama 3, Mistral, or Gemma 2, and vector databases (ChromaDB, Pinecone, or Qdrant) to develop cutting-edge solutions. Utilize Retrieval-Augmented Generation (RAG) frameworks (LangChain, LlamaIndex) to securely connect LLMs with organizational policies and data. Support the development and implementation of More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look , not just how they run) Comfort building MVPs that can More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look , not just how they run) Comfort building MVPs that can More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look, not just how they run) Comfort building MVPs that can More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look, not just how they run) Comfort building MVPs that can More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look, not just how they run) Comfort building MVPs that can More ❯