AI/ML Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer on a contract basis in London, requiring 7+ years of software engineering and applied ML experience. Key skills include Python, LangChain, ML/NLP, and cloud platforms like AWS.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
September 27, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Deployment #React #NLP (Natural Language Processing) #"ETL (Extract #Transform #Load)" #TensorFlow #PyTorch #AWS (Amazon Web Services) #Cloud #Scala #Data Pipeline #Transformers #Generative Models #Python #Langchain #MLflow #ML (Machine Learning) #Programming #FastAPI #HBase #Monitoring #Model Evaluation #Observability
Role description
Job Title: AI/ML Engineer
Location: London
HYBRID
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
Job Title: AI/ML Engineer
Location: London
HYBRID
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
