Sanderson

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 3-6 month contract, offering £700-750/day. It requires strong SQL and Python skills, experience with GCP, and expertise in ML algorithms, data transformation, and debugging in production environments. Fully remote.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
750
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🗓️ - Date
November 28, 2025
🕒 - Duration
3 to 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
United Kingdom
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🧠 - Skills detailed
#Logistic Regression #Data Science #SQL (Structured Query Language) #NLP (Natural Language Processing) #Python #Matplotlib #ML (Machine Learning) #Pandas #Cloud #Regression #Computer Science #Jupyter #Deep Learning #dbt (data build tool) #Airflow #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #Debugging #BERT #Forecasting
Role description
Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 3-6 month initial Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth. With 40% of sales from sustainable products, this is a company that combines scale, innovation and purpose. As a Machine Learning Engineer, you’ll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows and ML issues in live production environments. We’re looking for individuals with: • Experience: Proven background as a Machine Learning Engineer. • Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). • Data transformation & manipulation: experience with Airflow, DBT and Kubeflow • Cloud: Experience with GCP and Vertex AI (developing ML services). • Expertise: Solid understanding of computer science fundamentals and time-series forecasting. • Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning).