Machine Learning Engineer (Mid/Senior Level)
Role: Machine Learning Engineer
Contract: 6 months
Rate: 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:
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Core Skills:
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Solid understanding of computer science fundamentals, including data structures, algorithms, data modeling, and software architecture.
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Proficiency in classical machine learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost) and modern deep learning algorithms (e.g., BERT, LSTM).
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Strong knowledge of SQL and Python's data analysis ecosystem (Jupyter, Pandas, Scikit-Learn, Matplotlib).
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Advanced Techniques:
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Familiarity with ensemble methods like bagging and boosting.
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Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data).
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Knowledge of summary, robust, and nonparametric statistics; hypothesis testing, probability distributions, sampling techniques, and stochastic processes.
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Cloud and Deployment:
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Proven experience in delivering high-quality AI-based products and productionising machine learning models.
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Experience developing cloud-based machine learning services, preferably using Google Cloud Platform (GCP).
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Problem-Solving and Coding:
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Ability to solve coding problems efficiently, implement vector operations, and use similarity measures like cosine similarity.
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Practical understanding of monkeypatching for runtime code modification.
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Soft Skills:
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Excellent communication skills, with the ability to articulate technical concepts clearly and manage stakeholder expectations.
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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!