16 of 16 Remote Permanent Weaviate Jobs

or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers, or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation of large language models. Comfortable with cloud platforms (Azure preferred), CI/CD tools, and More ❯

modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker More ❯

modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker More ❯

vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS SageMaker, Azure ML, Google Vertex AI APIs & Orchestration: OpenAI API, Anthropic Claude, Weaviate, FastAPI (for AI applications) MLOps & Experimentation: Weights & Biases, DVC (Data Version Control), Docker, Kubernetes General 2+ years of professional experience in relevant fields. Experience mentoring, coaching, or teaching others in More ❯

you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation framework for search quality and answer accuracy (BLEU/ROUGE, human‐in‐the‐loop, automatic hallucination checks). Deploy & monitor services on GCP (Cloud Run … increments. Champion best practices in testing, secure data handling (NHS DSPT), and GDPR compliance. Tech you’ll use Python, FastAPI, LangChain/LlamaIndex, PostgreSQL + PGVector, Redis, Pinecone/Weaviate, Vertex AI, Cloud Run, Docker, Terraform, Prometheus/Grafana, GitHub Actions What we’re looking for Master’s degree in Computer Science, Software Engineering, or related field; or equivalent practical More ❯

you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation framework for search quality and answer accuracy (BLEU/ROUGE, human‐in‐the‐loop, automatic hallucination checks). Deploy & monitor services on GCP (Cloud Run … increments. Champion best practices in testing, secure data handling (NHS DSPT), and GDPR compliance. Tech you’ll use Python • FastAPI • LangChain/LlamaIndex • PostgreSQL + PGVector • Redis • Pinecone/Weaviate • Vertex AI • Cloud Run • Docker • Terraform • Prometheus/Grafana • GitHub Actions What we’re looking for Master’s degree in Computer Science, Software Engineering, or related field; or equivalent practical More ❯

you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation framework for search quality and answer accuracy (BLEU/ROUGE, human‐in‐the‐loop, automatic hallucination checks). Deploy & monitor services on GCP (Cloud Run … increments. Champion best practices in testing, secure data handling (NHS DSPT), and GDPR compliance. Tech you’ll use Python • FastAPI • LangChain/LlamaIndex • PostgreSQL + PGVector • Redis • Pinecone/Weaviate • Vertex AI • Cloud Run • Docker • Terraform • Prometheus/Grafana • GitHub Actions What we’re looking for Master’s degree in Computer Science, Software Engineering, or related field; or equivalent practical More ❯

engineering, and deployment Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud Experience : AWS ecosystem knowledge (SageMaker, Lambda, etc.) Production Ready : ETL pipelines, version control, Agile methodologies It More ❯

user segmentation, etc.) Technical Skills: Proficient in Python, SQL, and data science libraries (Pandas, NumPy, Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps pipelines Solid understanding of NLP, LLM fine-tuning, and prompt engineering Preferred Qualifications Familiarity with customer analytics and marketing automation More ❯

teams (e.g., retrieval-augmented generation, prompt management, model orchestration). Work with embeddings, vector stores, and similarity search to enable contextual AI responses. Integrate with vector databases (e.g., FAISS, Weaviate, or Pinecone) to support semantic search and information retrieval. Build scalable APIs and services using FastAPI or similar frameworks. Use tools like MLflow to manage model experimentation, versioning, and deployment. … Proficiency in Python, with experience building services using FastAPI or similar frameworks. Working with embeddings for text or document representation and semantic search. Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone). Understanding of AI infrastructure: versioning, tracking, and deployment with tools like MLflow. Exposure to building production-grade APIs, services, or workflows in an agile, collaborative environment. Awareness of More ❯

RAG), and AI agents 💡 Build APIs, data pipelines, and backend components (mainly Python, FastAPI/Flask) 💡 Deploy microservice-friendly solutions, often in containerised setups (e.g. Docker) 💡 Work with ElasticSearch, Weaviate, Pinecone, and similar tools for vector search 💡 Solve problems, learn fast, and help us push the boundaries What we’re looking for: ✅ Enthusiasm and drive to learn — more important than More ❯

more specifically with: GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Weaviate (we use it for RAG in LLM powered tasks and for hybrid searches) Kubernetes (we run Weaviate and other specific services on Kubernetes) CircleCI DataDog Auth0 (we use it, but More ❯

Native (for Android & iOS) and Python Experience with Open Banking APIs (TrueLayer, Yapily, Salt Edge, etc.) Built or contributed to LLM-based recommendation systems Worked with vector databases (Pinecone, Weaviate, FAISS, Chroma) Familiar with embedding models (e.g. OpenAI, Sentence Transformers) This is a brilliant opportunity for someone who wants to contribute more than just writing code. The business are looking More ❯

Native (for Android & iOS) and Python Experience with Open Banking APIs (TrueLayer, Yapily, Salt Edge, etc.) Built or contributed to LLM-based recommendation systems Worked with vector databases (Pinecone, Weaviate, FAISS, Chroma) Familiar with embedding models (e.g. OpenAI, Sentence Transformers) Understands secure data practices (encryption, secure tokens, GDPR) This is a brilliant opportunity for someone who wants to contribute more More ❯

Native (for Android & iOS) and Python Experience with Open Banking APIs (TrueLayer, Yapily, Salt Edge, etc.) Built or contributed to LLM-based recommendation systems Worked with vector databases (Pinecone, Weaviate, FAISS, Chroma) Familiar with embedding models (e.g. OpenAI, Sentence Transformers) Understands secure data practices (encryption, secure tokens, GDPR) This is a brilliant opportunity for someone who wants to contribute more More ❯

Be a Great Fit If You: - Have 1-3 years experience building LLM/GenAI applications in production - Are fluent in Python, with hands-on experience in frameworks Transformers, Weaviate, Pinecone - Understand the trade-offs between prompt tuning, embedding search, fine-tuning, and structured knowledge grounding - Care deeply about user experience, not just model performance, you measure success by "does More ❯