Infinity Quest
AI/ML Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer on a contract basis, offering a pay rate of "X" for "Y" months. Key skills include Python, TensorFlow, PyTorch, LLMs, and experience with vector databases. Strong NLP and MLOps knowledge is required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
June 4, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Edinburgh, Scotland, United Kingdom
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🧠 - Skills detailed
#ML (Machine Learning) #GCP (Google Cloud Platform) #Data Science #Hugging Face #Python #NLP (Natural Language Processing) #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Monitoring #Docker #Model Deployment #Compliance #Databases #AWS SageMaker #Azure #PyTorch #Langchain #Deep Learning #Kubernetes #Classification #SageMaker #SQL (Structured Query Language) #TensorFlow #Deployment #Microservices #Data Engineering #Transformers #Programming #Scala #"ETL (Extract #Transform #Load)"
Role description
Key Responsibilities
• Design, develop, and deploy AI/ML solutions using Python and modern ML frameworks.
• Build and optimize Generative AI applications leveraging LLMs such as GPT, Claude, and Llama.
• Develop and maintain RAG-based systems using vector databases such as Pinecone, Weaviate, or ChromaDB.
• Implement NLP pipelines for document intelligence, entity extraction, text classification, semantic search, and conversational AI.
• Fine-tune, evaluate, and monitor machine learning and deep learning models.
• Build scalable MLOps pipelines for model deployment, monitoring, versioning, and governance.
• Collaborate with data scientists, architects, product owners, and business stakeholders to deliver AI-driven solutions.
• Implement AI governance, model explainability, bias detection, and compliance controls.
• Integrate AI solutions with enterprise systems through APIs and microservices.
Required Skills
• Strong programming skills in Python.
• Experience with TensorFlow, PyTorch, Hugging Face, LangChain, and LlamaIndex.
• Hands-on experience with LLMs, Generative AI, Prompt Engineering, and RAG architectures.
• Experience with Vector Databases (Pinecone, Weaviate, ChromaDB).
• Strong understanding of NLP, Deep Learning, Transformers, and Machine Learning algorithms.
• Experience with AWS SageMaker, Azure ML, or GCP Vertex AI.
• Knowledge of Docker, Kubernetes, CI/CD, and MLOps practices.
• Strong SQL and data engineering fundamentals.
Key Responsibilities
• Design, develop, and deploy AI/ML solutions using Python and modern ML frameworks.
• Build and optimize Generative AI applications leveraging LLMs such as GPT, Claude, and Llama.
• Develop and maintain RAG-based systems using vector databases such as Pinecone, Weaviate, or ChromaDB.
• Implement NLP pipelines for document intelligence, entity extraction, text classification, semantic search, and conversational AI.
• Fine-tune, evaluate, and monitor machine learning and deep learning models.
• Build scalable MLOps pipelines for model deployment, monitoring, versioning, and governance.
• Collaborate with data scientists, architects, product owners, and business stakeholders to deliver AI-driven solutions.
• Implement AI governance, model explainability, bias detection, and compliance controls.
• Integrate AI solutions with enterprise systems through APIs and microservices.
Required Skills
• Strong programming skills in Python.
• Experience with TensorFlow, PyTorch, Hugging Face, LangChain, and LlamaIndex.
• Hands-on experience with LLMs, Generative AI, Prompt Engineering, and RAG architectures.
• Experience with Vector Databases (Pinecone, Weaviate, ChromaDB).
• Strong understanding of NLP, Deep Learning, Transformers, and Machine Learning algorithms.
• Experience with AWS SageMaker, Azure ML, or GCP Vertex AI.
• Knowledge of Docker, Kubernetes, CI/CD, and MLOps practices.
• Strong SQL and data engineering fundamentals.
