Remote Machine Learning Engineer – Data Science & AI for Sustainable Growth

Sanderson United Kingdom
Remote
This Job is No Longer Active This position is no longer accepting applications
AI Summary

A fully remote, 3-6 month contract role within a forward-thinking FTSE 100 organization leveraging AI to enhance customer experience and optimize supply chains. The role involves maintaining and debugging core data and ML systems across Europe, focusing on reliability and performance. The ideal candidate has experience with SQL, Python, cloud ML services, and advanced ML algorithms.

Key Highlights
Remote 3-6 month contract for a Machine Learning Engineer in a FTSE 100 company
Focus on system stability, performance optimization, and troubleshooting in production
Strong technical skills required in SQL, Python, cloud ML platforms, and ML algorithms
Technical Skills Required
SQL Python Pandas Scikit-learn Jupyter Matplotlib Airflow DBT Kubeflow Google Cloud Platform Vertex AI ML algorithms Deep learning
Benefits & Perks
Competitive daily rate (£700-750/day)
Fully remote work
Short-term contract (3-6 months)

Job 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).


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