Machine Learning Engineer

Machine Learning Engineer (Mid/Senior Level)

Role: Machine Learning EngineerContract: 6 monthsRate: Up to £800 per day (Inside IR35)Location: One day per week based in London

Role Purpose:Join our Data Science team to establish best practices and develop/deploy core ML/AI algorithms. As a Machine Learning Engineer, you will tackle data science challenges, trailblaze the development of algorithms, and support commercial goals through innovative data science approaches.

Key Accountabilities / Responsibilities:

• Lead the implementation of data science projects, developing algorithms and data science approaches to support commercial objectives.
• Collaborate across banners and group functions to build a data science roadmap that minimises time to value and maximises long-term effectiveness.
• Collaborate with tech, product, and data teams to develop data platforms that embed data science directly into our products and processes.

Required Skills & Experience:

• Core Skills:
  • Solid understanding of computer science fundamentals, including data structures, algorithms, data modeling, and software architecture.
  • Proficiency in classical machine learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost) and modern deep learning algorithms (e.g., BERT, LSTM).
  • Strong knowledge of SQL and Python's data analysis ecosystem (Jupyter, Pandas, Scikit-Learn, Matplotlib).
• Advanced Techniques:
  • Familiarity with ensemble methods like bagging and boosting.
  • Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data).
  • Knowledge of summary, robust, and nonparametric statistics; hypothesis testing, probability distributions, sampling techniques, and stochastic processes.
• Cloud and Deployment:
  • Proven experience in delivering high-quality AI-based products and productionising machine learning models.
  • Experience developing cloud-based machine learning services, preferably using Google Cloud Platform (GCP).
• Problem-Solving and Coding:
  • Ability to solve coding problems efficiently, implement vector operations, and use similarity measures like cosine similarity.
  • Practical understanding of monkeypatching for runtime code modification.
• Soft Skills:
  • Excellent communication skills, with the ability to articulate technical concepts clearly and manage stakeholder expectations.
  • Strong interpersonal skills, able to work collaboratively in a team and mentor junior members.

How to Apply:If you are passionate about data science and machine learning, possess the necessary skills and experience, and are ready to take on a challenging role, please apply below!