and 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 More ❯
patterns specific to RAG (Retrieval-Augmented Generation), Graph RAG, Agentic RAG, and multi-agent systems. Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS). Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for More ❯
Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding of data paradigms for LLMs, RAG architectures, and how data pipelines support fine-tuning or pre-training. MLOps Principles More ❯
internal workflows using Azure or Vertex AI, with secure data handling. Implement ISO-aligned controls, monitor infrastructure, and respond to cloud security incidents. Work with tools like Airflow, Dataflow, Pinecone, and ElasticSearch to manage secure data flows. What You'll Need 3+ years in DevSecOps, DevOps, or Site Reliability Engineering , with a strong security background. Expertise in GitHub Actions, Terraform More ❯
largescale transformer models (BERT, GPT) and promptengineering for sentiment tasks Background building activelearning and annotation pipelines to bootstrap training data Familiarity with semantic search or vector databases (Elasticsearch, FAISS, Pinecone) for topic modeling and similarity queries Familiarity with crypto markets, order books, and risk-management frameworks Familiarity with anomalydetection methods for streaming text and timeseries data Experience developing EVM smart More ❯
new tech quickly Experience mentoring junior engineers Experience interacting with multiple stakeholders Enjoyable to work with TECHNOLOGY STACK Python, PostgreSQL, FastAPI, Redis, TypeScript, React, Next.js, Tailwind, AWS, Kubernetes, Prometheus, Pinecone, GPT-4 EXAMPLE PROJECTS Craft plan to measure and improve our search engine Improve and migrate our data model for the content we host Migrate our NLP algorithms over to More ❯
prompt tweaks changed an LLM's output to match a specific product need. Nice-to-Haves LangChain, LlamaIndex, or any RAG experiment on your GitHub. Vector database dabbling (pgvector, Pinecone). A side project people outside your family have used. Our Stack React 18 Next.js Node 20 FastAPI OpenAI & Anthropic APIs Postgres + pgvector Vercel Fly.io GitHub Actions Cursor & Windsurf More ❯
Strong sense of UX Good systems design Ability to learn new tech quickly Enjoyable to work with TECHNOLOGY STACK Python, PostgreSQL, FastAPI, Redis, TypeScript, React, Next.js, Tailwind, AWS, Kubernetes, Pinecone, GPT-4 EXAMPLE PROJECTS Use an LLM to identify references to other sections in the text of the law Create Rap Genius-style annotations on sections of building code, to More ❯
solving complex problems Good systems design Ability to learn new tech quickly Enjoyable to work with TECHNOLOGY STACK Python, PostgreSQL, FastAPI, Redis, TypeScript, React, Next.js, Tailwind, AWS, Kubernetes, Prometheus, Pinecone, GPT-4 EXAMPLE PROJECTS Use an LLM to identify references to other sections in the text of the law Improve and migrate our data model for the content we host More ❯
controllers. Develop and maintain AI microservices using Docker, Kubernetes, and FastAPI, ensuring smooth model serving and error handling; Vector Search & Retrieval: Implement retrieval-augmented workflows: ingest documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features. Rapid Prototyping: Create interactive AI demos and proofs-of-concept with Streamlit, Gradio, or Next.js for stakeholder feedback; MLOps & Deployment: Implement CI/… experience fine-tuning LLMs via OpenAI, HuggingFace or similar APIs; Strong proficiency in Python; Deep expertise in prompt engineering and tooling like LangChain or LlamaIndex; Proficiency with vector databases (Pinecone, FAISS, Weaviate) and document embedding pipelines; Proven rapid-prototyping skills using Streamlit or equivalent frameworks for UI demos. Familiarity with containerization (Docker) and at least one orchestration/deployment platform More ❯
