Note: The job is a remote job and is open to candidates in USA. Qcells North America is seeking a highly skilled Staff AI Engineer to join their Grid & Energy Analytics team, focusing on the intersection of artificial intelligence and energy management. The role involves developing and deploying AI solutions to optimize energy systems and enhance forecasting capabilities.

Responsibilities

• Machine Learning Model Development and Deployment: Design, develop, and deploy various types of forecasts, including those for energy market prices and ancillary service prices, energy demand, renewable energy resource generation forecasting like PV and Wind
• Design and implement Agentic AI systems: Design and implement Agentic AI systems for autonomous energy management. This includes building intelligent agents that make real-time decisions to optimize energy usage and generation
• Research and Innovation: Stay ahead of the curve by conducting creative research to identify and implement new machine learning approaches that improve model performance and platform metrics
• Develop and deploy robust MLOPs pipelines: Identify, integrate, and manage new data sources to enhance model performance. Ensure the scalability and reliability of all data pipelines. Contribute to the design and development of our internal forecasting platform, supporting the entire machine learning development lifecycle and hosting models in production
• Production Support: Provide ongoing support for production models, including monitoring performance, troubleshooting issues, and resolving production-related problems to ensure reliability and uptime
• Team Collaboration: Partner closely with other teams to ensure that our machine learning and Agentic AI solutions deliver end-to-end value
• Energy Domain Knowledge: Apply knowledge of power systems modeling to create accurate and reliable AI solutions that consider the physical constraints and dynamics of energy grids

Skills

• A higher degree (Master's or Ph.D.) is preferred, with a focus on machine learning, statistics, or related mathematics
• Proficiency in Python with at least 5 years of experience in software development. You should be familiar with agile development practices and be able to write production-quality code
• Extensive experience in developing, deploying, and maintaining machine learning models in production, particularly for time series forecasting, clustering, classification applications
• Theoretical and practical experience with a variety of forecasting algorithms and approaches, including statistical, regression, and deep learning algorithms. You should be able to select the most appropriate model for a given application
• Experience with cloud-hosted systems and related tooling, preferred in Azure/Fabric, including compute services, container orchestration, and various database and data warehouse platforms
• Expertise with relevant Python Machine Learning libraries such as pandas, numpy, xgboost, lightgbm, pytorch, keras, scipy, statsmodels, transformers, nixtla, sklearn, plotly, seaborn, bokeh, and so on
• Experience with setting up RAG (Retrieval-Augmented Generation) pipelines, fine-tuning, and deploying domain-specific models and agents
• Intrinsic motivation and a passion for learning, collaboration, and working in the clean energy space
• Travel may be required up to 10%, depending on business needs
• Experience with power systems modeling, including concepts like security-constrained economic dispatch, unit commitment, or power flow models
• Prior domain expertise in forecasting, analysis, or trading within electricity markets, such as ERCOT, CAISO, PJM, and others
• Familiarity with energy storage and renewable asset optimization modeling

Company Overview

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