Senior ML Engineer

London Source: WhatJobs
£90,000–£150,000

SENIOR MACHINE LEARNING ENGINEER

LOCATION: Central London

SALARY: Negotiable

WAY OF WORKING: Full Time | Contract | Hybrid Working

THE SENIOR MACHINE LEARNING ENGINEER OPPORTUNITY

  • Design, develop, and deploy scalable machine learning systems that support demand forecasting and related AI products.
  • Build and maintain end-to-end ML pipelines covering data preparation, experimentation, training, evaluation, deployment, monitoring, and optimisation.
  • Develop large-scale data processing and feature engineering solutions using technologies such as PySpark and Databricks.
  • Create multimodal machine learning models that combine image, text, metadata, and behavioural data to enhance forecasting and AI capabilities.
  • Collaborate with Applied Scientists, Data Engineers, Product Managers, and business stakeholders to productionise innovative machine learning solutions.

YOUR KEY SKILLS

  • Significant experience designing, deploying, and supporting machine learning systems in production environments.
  • Strong Python software engineering expertise, including testing, code quality, and maintainable application development.
  • Proven experience working with large-scale data processing technologies such as PySpark and Databricks.
  • Strong background building end-to-end ML pipelines across the full machine learning lifecycle.
  • Hands-on experience with deep learning frameworks including PyTorch, TensorFlow, or equivalent technologies.
  • Experience with multimodal machine learning, embedding models, representation learning, or foundation models.
  • Strong understanding of modern deep learning architectures, particularly Transformers and large-scale representation learning techniques.
  • Experience working with distributed computing environments, large datasets, and scalable training or inference systems.
  • Knowledge of cloud platforms and modern MLOps practices.
  • Excellent communication skills with the ability to work effectively across technical and non-technical teams.
  • Pragmatic approach to balancing engineering excellence with business outcomes.

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