Python Engineer (AI/ML)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Python Engineer (AI/ML) with a contract length of "unknown," offering a pay rate of "unknown." Key skills include advanced Python, API integration, ML/AI solutions, and NLP techniques. Experience with RAG architectures and frameworks like LangChain is required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
September 3, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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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
#Flask #NER (Named-Entity Recognition) #Kafka (Apache Kafka) #API (Application Programming Interface) #FastAPI #Debugging #AI (Artificial Intelligence) #Microservices #ML (Machine Learning) #REST (Representational State Transfer) #Langchain #Classification #NLP (Natural Language Processing) #Scala #Databases #Python #Azure
Role description
You have:
· Advanced Python proficiency, especially in scalable, clean code architecture and microservices (e.g., FastAPI, Flask, asyncio)
· Solid understanding of API integration patterns and inter-servic communication (e.g. REST, Kafka)
· Experience with authentication and authorization mechanisms (e.g. OAuth2, JWT, Azure AD)
· At least two ML/AI solutions delivered to production, ideally involving document understanding, NLP or search/retrieval systems
· Practical knowledge and hands-on experience with: RAG architectures, LLMs (e.g., OpenAI, Antropic), Vector databases (e.g., FAISS, Azure AI Search), Embeddings (e.g., OpenAI)
· Strong grasp of NLP techniques: named entity recognition (NER), document classification, chunking, summarization, question answering.
· Ability to evaluate trade-offs and select appropriate ML/AI techniques for a given problem.
· Experience with PoC development and iterating quickly based on results.
· Familiarity with LangChain, LlamaIndex, or similar agentic frameworks.
· Strong debugging, profiling, and optimization skills for AI applications.
You have:
· Advanced Python proficiency, especially in scalable, clean code architecture and microservices (e.g., FastAPI, Flask, asyncio)
· Solid understanding of API integration patterns and inter-servic communication (e.g. REST, Kafka)
· Experience with authentication and authorization mechanisms (e.g. OAuth2, JWT, Azure AD)
· At least two ML/AI solutions delivered to production, ideally involving document understanding, NLP or search/retrieval systems
· Practical knowledge and hands-on experience with: RAG architectures, LLMs (e.g., OpenAI, Antropic), Vector databases (e.g., FAISS, Azure AI Search), Embeddings (e.g., OpenAI)
· Strong grasp of NLP techniques: named entity recognition (NER), document classification, chunking, summarization, question answering.
· Ability to evaluate trade-offs and select appropriate ML/AI techniques for a given problem.
· Experience with PoC development and iterating quickly based on results.
· Familiarity with LangChain, LlamaIndex, or similar agentic frameworks.
· Strong debugging, profiling, and optimization skills for AI applications.
