Principal Machine Learning Engineer

You will lead multiple live applications of machine learning (ML) while influencing future product development. This role will be a great mix of technical leadership, application and data pipeline design, and hands-on work with our data science and application engineering team members.

 

Gradiant has quickly become the water industry’s first choice to optimize desalination and water reuse using ML, so this role will be integral to our ongoing results and innovation.

 

 

Essential Duties & Responsibilities:

  • Technical leadership to develop and drive ML best practices, manage strategic ML projects and mentor team members
  • Work with large, time series data sets
  • Research and implement appropriate ML algorithms and related tools for scalability
  • Test, validate and maintain ML models, data pipelines and related applications built on Google tools and related technologies
  • Work with data science to facilitate data analysis and visualizations
  • Evaluate the meaningfulness of specific methods and techniques for given ML problems and edge cases
  • Create software designed, implemented and tested in accordance with our engineering standards
  • Maintain methods for baselining and continuous model validation
  • Work with teammates to discover greater efficiency in existing solutions

 

Requirements:

  • Bachelor/Master/PhD in Mathematics, Statistics, Computer Science, Economics, Physics, Engineering, or related discipline
  • 10+ years of work experience, with 2-3+ years in a senior role delivering ML for practical applications
  • Experience using a Python ML stack (pandas, scikit-learn, Jupyter, etc.), GCP, Kubernetes, Docker containers
  • Experience working with at least one major ML framework e.g. PyTorch, TensorFlow
  • Knowledge of multiple ML techniques and the ability to efficiently select the correct model to test, tune and deploy
  • Time series or process data experience and ANNs to high accuracy
  • Prior experience in data science and/or data engineering (building ML pipelines) is advantageous
  • Prior experience in process automation or industrial process engineering is good-to-have
  • Prior formal team management, coaching or mentorship is good-to-have
  • Strong writing, presenting and listening skills with the ability to communicate complicated concepts to peers around the world