Lead Machine Learning Engineer

Opus Recruitment Solutions
London
3 weeks ago
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Role :Lead Machine Learning Engineer

Salary :£80,000 - £100,000 + Equity


The Company :


Our client are revolutionising the satellite industry, a critical sector that underpins global communication, navigation, and data collection. Despite its importance, the industry is ripe for digital transformation.


Our client captures and analyses high-frequency data from satellites to enhance risk assessment, prevent equipment failures, and optimize operational efficiency. They are in search of a visionary leader to spearhead AI initiatives and significantly enhance their predictive capabilities.


The Role


  • Design, build, and implement advanced AI solutions
  • Work closely with engineering teams to bring models into production and enhance their performance
  • Lead and mentor the data science team in creating innovative predictive models
  • Collaborate with the CTO to shape the data science strategy and roadmap, identifying untapped potential in our datasets and the global satellite network


You Should…


  • Have extensive experience in machine learning and statistical modelling
  • Have a proven track record of building and deploying ML models in production environments, with strong CI/CD skills
  • Be proficient in Python and its data science ecosystem (pandas, scikit-learn, TensorFlow/PyTorch)
  • Have a solid understanding of time series analysis and anomaly detection
  • Possess excellent communication skills to explain complex concepts to various stakeholders
  • Have demonstrated experience leading data science initiatives
  • Be passionate about solving complex problems with messy, real-world data


Ideally, You…


  • Have experience with large-scale sensor data and real-time analytics
  • Have a solid understanding of physics and mechanical principles
  • Stay engaged with the rapidly-evolving AI ecosystem
  • Have experience with NoSQL databases (MongoDB) and platforms like Azure ML and Databricks
  • Have expertise in signal processing and condition monitoring
  • Have startup experience or have worked in fast-paced, startup-like environments

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