Machine Learning Engineer - Forecasting & Cloud Applications

We are seeking a Machine Learning Engineer with strong forecasting skills and hands-on experience maintaining cloud-based applications. This role combines developing forecasting models with maintaining a SaaS application that uses Supabase, Render, and Docker.

We are looking for someone who can take ownership of both the modeling work and the infrastructure needed to keep it running reliably, not someone focused solely on research, generative AI, or RAG pipelines.

Responsibilities

• Develop machine-learning models to forecast electricity generation and market participants bidding patterns using historical electricity-market data, weather forecasts, and operating data from individual energy assets.
• Develop and evaluate machine-learning models for time-series forecasting, using tools such as CatBoost, XGBoost, and LightGBM.
• Conduct reproducible, out-of-sample backtests and report forecast performance.
• Integrate forecasting models and data pipelines into the existing SaaS application.
• Maintain databases and data workflows using Supabase.
• Build and maintain Docker-based development and deployment workflows.
• Manage deployments and troubleshoot application issues on Render.
• Monitor application and pipeline performance, investigate failures, and improve reliability.
• Maintain documented code, deployment procedures, and operating workflows.

Required qualifications

• Bachelor's or Master's degree in Computer Science or a related field.
• Minimum of three years of relevant professional experience in machine-learning development and software engineering.
• Demonstrated experience developing, backtesting, and deploying time-series forecasting models.
• Strong Python skills in data processing, feature engineering, and machine learning.
• Strong SQL skills and hands-on experience with database design, queries, and maintenance.
• Practical experience with Supabase, Render, and Docker or similar tools.
• Experience maintaining production applications, troubleshooting deployments, and managing cloud environments.

Preferred qualifications

• Experience with electricity markets, energy data, or renewable generation forecasting.
• Experience forecasting participant bidding behavior, order-book dynamics, auction bids, or price-quantity offer patterns from historical data.
• Experience maintaining SaaS applications and supporting production users.

Key attributes and mindset

• Takes ownership of assigned work and follows through on commitments.
• Works effectively in a fast-paced startup environment with clear daily deliverables.
• Brings an entrepreneurial mindset and a practical approach to problem-solving.
• Is committed to high-quality work and reliable application operation.

How to apply

Email your resume to [HIDDEN TEXT] with the subject line Machine Learning Engineer - Forecasting & Cloud Applications.

Briefly describe:

• One forecasting model you personally developed and how you backtested it.
• One production application or ML pipeline you deployed or maintained.
• Your hands-on experience with Supabase, Render, and Docker or similar tools.

We will prioritize applications that include both a resume and a relevant project description.

Compensation

Base salary: 6–9 LPA (based on experience)

About the Company

NewGrid Consulting is driven by a bold vision: a smarter, more efficient energy future. Our mission is to help electric utilities, regulators, developers, and other power industry stakeholders make better planning and investment decisions for the electric grid. Alongside delivering high-impact consulting services, we are building cutting-edge software and analytics platforms that will shape the future of electric infrastructure planning, grid reliability, and energy market intelligence.