Lead Engineer, Disciplinary Engineering And Science - Mathematics & Data Science

Baker Hughes

Hybrid
Ai algorithms for regression classification anomaly detection
Time series data analysis with uncertainty quantification
Python c++ programming languages
Baker Hughes is seeking a Lead Engineer in Disciplinary Engineering and Science, specializing in Mathematics and Data Science, with a focus on AI applications in energy transformation. The role involves collaborating with multidisciplinary teams to develop AI-driven engineering solutions while working in a hybrid environment

Job Summary

  • You will be instrumental in the mission to make energy safer, cleaner, and more efficient through intelligent technologies.
  • The role involves collaborating with multidisciplinary teams to define new AI-powered engineering workflows for product optimization and simulation.
  • This is a remote role offering flexible working patterns with occasional travel to local virtual ports.

Matching Summary

Match Score: 85

Baker Hughes is seeking a Lead Engineer in Disciplinary Engineering and Science, specializing in Mathematics and Data Science, with a focus on AI applications in energy transformation. The role involves collaborating with multidisciplinary teams to develop AI-driven engineering solutions while working in a hybrid environment.

Skills & Requirements

Must-have

  • AI algorithms for regression classification anomaly detection
  • Time series data analysis with uncertainty quantification
  • Python C++ programming languages
  • Model deployment techniques edge serving
  • Optimization algorithms active learning
  • Traditional control algorithms MPC RL

Nice-to-have

  • Experience with agentic frameworks
  • Knowledge of turbomachinery thermodynamics
  • Background in rotor dynamics chemistry
  • Test Driven Development Agile methods
  • 3D Graph data modeling experience

Key Requirements

  • Deep understanding of ML and AI algorithms
  • Proven experience applying AI to dynamical data sources
  • Working knowledge of model deployment and edge serving
  • Experience combining models from different sources

Work Rights

Not specified

Tailored Resume

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