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
- Strong foundation in statistical methods and deep learning
- Hands-on experience with large-scale data environments
- 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.