Opus Recruitment Solutions

ML Engineer - 6 Month Contract

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML Engineer on a 6-month contract, paying £400 - £500 daily. Remote work is required with occasional London travel. Key skills include Python, machine learning model deployment, and experience with frameworks like LangChain and cloud AI services.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
October 29, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Inside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
London
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🧠 - Skills detailed
#ML (Machine Learning) #TensorFlow #Keras #AI (Artificial Intelligence) #Python #Langchain #Observability #PyTorch #Transformers #Deep Learning #Pandas #API (Application Programming Interface) #Programming #Libraries #"ETL (Extract #Transform #Load)" #Cloud #Azure
Role description
I am working with a consultancy feeding into the public sector, looking for multiple ML Engineers. Inside IR35 £400 - £500 per day (depending on experience level) Remote (occasional London travel) • Proven experience building and deploying machine learning models in a production environment. • Strong programming skills and deep expertise in Python. • Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. • Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). • Practical experience using managed AI services and foundation models from a major cloud provider (e.g., Amazon Bedrock, Google Vertex AI, Azure AI Services). • Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). • A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: • Working with tools/interfaces for AI applications e.g. MCP protocol. • Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA. • Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI) • Experience with observability and evaluation tools for LLMs such as TruLens or Helicone. • Experience with AI safety and reliability frameworks like Guardrails AI.