Elevate utility operations as a Machine Learning Engineer with Themis Intelligence. Drive advanced intelligence systems development that integrates time-series and geospatial data for critical grid environments.
In this hybrid role, you'll work full time contributing to scalable machine learning systems. Your expertise in time-series modeling and MLOps practices will shape robust production pipelines from architecture to deployment. Join a team committed to operational reliability and evidence-based development for effective utility management.
Key Responsibilities:
• Develop advanced machine learning models and data systems
• Implement production-grade pipelines in cloud and on-premises
• Integrate time-series data and geospatial signals
• Contribute to architecture decisions for machine learning systems
• Ensure operational reliability and benchmark validation
Requirements:
• Bachelor’s degree in relevant technical field or equivalent experience
• 3+ years in machine learning or applied AI
• Robust foundation in statistical methods and deep learning
• Hands-on experience with large-scale data settings
• Proficiency in Python-based ML tools like TensorFlow
Bring your machine learning expertise to Themis Intelligence, shaping the future of utility operations with data-driven solutions.
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