AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer with 10+ years of IT experience, focusing on API integration, ML/AI solutions, and NLP techniques. Contract length and pay rate are unspecified. Remote work is allowed. Key skills include RAG architectures and LLMs.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
-
🗓️ - Date discovered
August 9, 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
#API (Application Programming Interface) #Libraries #REST (Representational State Transfer) #Debugging #Kafka (Apache Kafka) #AI (Artificial Intelligence) #NLP (Natural Language Processing) #Classification #Langchain #ML (Machine Learning) #Azure #NER (Named-Entity Recognition) #Databases
Role description
About the Role:
Must have:
• Candidate with 10+ yrs of experience over all IT
Responsibilities:
• Solid understanding of API integration patterns and inter-service 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.
GOOD TO HAVE:
• Experience with OCR libraries like Tesseract or Azure Form Recognizer.
Required Skills:
• Solid understanding of API integration patterns and inter-service 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.
Preferred Skills:
• Experience with OCR libraries like Tesseract or Azure Form Recognizer.
About the Role:
Must have:
• Candidate with 10+ yrs of experience over all IT
Responsibilities:
• Solid understanding of API integration patterns and inter-service 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.
GOOD TO HAVE:
• Experience with OCR libraries like Tesseract or Azure Form Recognizer.
Required Skills:
• Solid understanding of API integration patterns and inter-service 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.
Preferred Skills:
• Experience with OCR libraries like Tesseract or Azure Form Recognizer.
