Senior Machine Learning Engineer

London  ‐ Onsite
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Machine Learning Data Science Algorithms Artificial Intelligence Statistics Cloud Computing Deep Learning Innovation Algorithm Design Data Analysis Data Modeling Data Structures Statistical Hypothesis Testing Python (Programming Language) Logistic Regression Software Architecture Stochastic Process SQL Databases Standardization Google Cloud Bagging Random Forest Jupyter Pandas Matplotlib Scikit Learn Banner Advertisement Xgboost Data Management


Senior Machine Learning Engineer

6 months
£800 - £1000 per day (Inside IR35)
One day per month based in London

Role Purpose:
Join our client's Data Science team and work with exciting new technologies in machine learning and AI. Develop and deploy core ML/AI algorithms to drive innovation. As a Senior Machine Learning Engineer, you will tackle complex data science challenges, pioneer algorithm development, and support commercial objectives with cutting-edge data science solutions.

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 modelling, and software architecture.
    • Proficiency in classical machine learning algorithms (eg, Logistic Regression, Random Forest, XGBoost) and modern deep learning algorithms (eg, 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.

Please access the link below to apply or email your CV across to (see below)

Start date
Sanderson Recruitment Plc
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