1 to 25 of 39 Permanent Weaviate Jobs

Kubernetes Agile tools: Jira AI/ML Tools & Frameworks: LLM Frameworks: LangChain, LangGraph, LlamaIndex Model APIs: OpenAI, Anthropic Claude, Google Gemini Vector Databases: Pinecone, Weaviate, FAISS, Chroma MLOps & Experimentation: MLflow, Kubeflow, Weights & Biases Data Processing: Pandas, NumPy, Apache Spark Deployment & Serving: TorchServe, TensorFlow Serving, BentoML Prompt Engineering & RAG pipelines (Retrieval ...

prompt engineering and evaluation techniquesExperience building enterprise-grade GenAI applications3. RAG (Critical Requirement)Proven experience designing and implementing RAG architecturesExperience with vector databases (Pinecone, Weaviate, etc.)Ability to integrate domain-specific data into AI systems4. Agentic AI/AI AgentsExperience building AI agents/multi-agent systemsFamiliarity with orchestration frameworks ...

functional teams within a fast-paced environment Nice to Have Experience within financial services or other regulated industries Exposure to vector databases (e.g. Pinecone, Weaviate, FAISS) Experience with MLOps/LLMOps and deploying models into production Familiarity with LLM fine-tuning, evaluation, or guardrailing techniques Experience building internal tools such ...

/CD pipelines for software or ML systems using tools such as GitHub Actions, Jenkins, or CircleCI. Experience with RAG systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models. Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code tools such as Terraform or Pulumi. ...

pipelines for unstructured text data, including scraping, cleaning, deduplication, and transformation for LLM training. Build and maintain vector search solutions (e.g., Pinecone, Milvus, Weaviate, Chroma) to store and retrieve embeddings for RAG systems. Prepare high-quality datasets for fine-tuning adapters (e.g., LoRA) and train LLMs using frameworks like PyTorch ...

HuggingFace, etc.) into production systems Develop secure, high-performance REST/GraphQL APIs Work with vector databases and traditional data stores (Postgres, Redis, Pinecone, Weaviate, etc.) Implement authentication, authorization, and observability best practices Deploy and maintain cloud infrastructure on AWS/GCP/Azure Collaborate with ML engineers on model ...

LangSmith, or similar LLM observability platforms. Experience creating evaluation frameworks using RAGAS, G-Eval, or custom rubric systems. Strong familiarity with vector databases (Pinecone, Weaviate, Milvus), embeddings, and retrieval pipelines. Solid understanding of LLM architectures, tokenization, embeddings, context limits, and RAG patterns. Experience in cloud (GCP preferred), Kubernetes/ ...

pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate and Chroma, and tuning embedding models for enterprise data. Building agentic systems using frameworks like LangGraph, Semantic Kernel, LangChain, LlamaIndex and AutoGen tool use, function calling ...

pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate and Chroma, and tuning embedding models for enterprise data. Building agentic systems using frameworks like LangGraph, Semantic Kernel, LangChain, LlamaIndex and AutoGen tool use, function calling ...

manage infrastructure across AWS, GCP, or Azure using Docker and modern hosting platforms (Vercel, Netlify) Work with vector databases and data systems (PostgreSQL, Pinecone, Weaviate, FAISS) Collaborate with stakeholders and communicate complex concepts clearly Document solutions and enable clean handoff for internal teams Engagement Brief This consulting engagement is focused ...

LangChain, or LlamaIndex. Background or interest in Civil Engineering, BIM (Building Information Modeling), or CAD software integration. Experience with Vector Databases (e.g., Pinecone, Weaviate, or pgvector). ...

Google Cloud AI services (Vertex AI, Gemini, PaLM) - Strong understanding of prompt engineering and LLM optimization techniques Data & Storage - Proficiency with vector databases (Pinecone, Weaviate, Chroma, or similar) - Experience with traditional databases (PostgreSQL, MongoDB) - Knowledge of data ingestion frameworks and ETL pipelines - Understanding of embedding models and semantic search optimization ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence ...

regulated, real-time model deployment Preferred Qualifications: Experience integrating with Epic, HL7, FHIR, and SMART-on-FHIR Working knowledge of LLMs. GenAl tools. LangChain, Weaviate, or ChromaRB ...

Transformers LLM Frameworks: LangChain, LlamaIndex, OpenAI SDK Agentic AI (Good to Have): LangGraph, AutoGen, CrewAI Data & SQL: Oracle, MySQL, SQLAlchemy Vector Databases: FAISS, Pinecone, Weaviate, Qdrant LLMOps/MLOps (Good to Have): MLflow, Weights & Biases, BentoML, Airflow Thanks & Regards Gunjan Sharma Sr. Technical Recruiter Email: Kanak IT is an equal ...

experience of: Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use Python/TypeScript: Primary languages for agent + backend development ...

pilot environments (e.g., using FastAPI, Flask, or Streamlit) Strong understanding of embeddings, prompt chaining, and pipeline orchestration Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) Comfortable with rapid iteration, MVP mindset, and cross-functional collaboration Prior exposure to multilingual or low-resource language challenges is a plus Preferred Qualifications: Experience ...

capabilities across the platform — from content generation to account intelligence and campaign automation. Design and implement RAG pipelines using vector databases like Qdrant or Weaviate for contextual awareness and retrieval. Build robust backend services in TypeScript to serve AI-driven features, including streaming, tool use, and human-in-the-loop ...