Resource Informatics Group
Job Title:
AI/ML Engineer Location:
London/NY time zone hours / Canada Job Type:
Contract
Required Qualifications 7+ years in software engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertise. Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration. Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; solid understanding of software engineering fundamentals and secure development. Experience with AI agent frameworks and MCP; familiarity with agent observability (LangSmith/LangFuse) and agentic RAG patterns Track record of delivering scalable, production AI systems and collaborating across teams. Experience with agent frameworks (AutoGen, CrewAI), tool-use ecosystems, and advanced planning/reasoning strategies Knowledge of cloud platforms (AWS), MLOps, and data pipelines; React.js familiarity is a plus. Exposure to enterprise environments and secure, compliant deployments
Key Skills
Programming : Python; backend APIs (FastAPI) AI/ML : ML/NLP, generative AI, embeddings, model evaluation Frameworks : LangChain, LangGraph; plus LlamaIndex, PyTorch, TensorFlow, MLflow Architectures : RAG, Transformers, OCR Agents : Design and orchestration, memory/state management, tool integration; MCP and agent-to-agent protocols Observability : LangSmith/LangFuse for agent monitoring
AI/ML Engineer Location:
London/NY time zone hours / Canada Job Type:
Contract
Required Qualifications 7+ years in software engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertise. Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration. Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; solid understanding of software engineering fundamentals and secure development. Experience with AI agent frameworks and MCP; familiarity with agent observability (LangSmith/LangFuse) and agentic RAG patterns Track record of delivering scalable, production AI systems and collaborating across teams. Experience with agent frameworks (AutoGen, CrewAI), tool-use ecosystems, and advanced planning/reasoning strategies Knowledge of cloud platforms (AWS), MLOps, and data pipelines; React.js familiarity is a plus. Exposure to enterprise environments and secure, compliant deployments
Key Skills
Programming : Python; backend APIs (FastAPI) AI/ML : ML/NLP, generative AI, embeddings, model evaluation Frameworks : LangChain, LangGraph; plus LlamaIndex, PyTorch, TensorFlow, MLflow Architectures : RAG, Transformers, OCR Agents : Design and orchestration, memory/state management, tool integration; MCP and agent-to-agent protocols Observability : LangSmith/LangFuse for agent monitoring