[Hiring] Machine Learning Engineer @Remote World

Role Description

You'll build, evaluate and deploy machine learning models that improve energy forecasting accuracy. Working alongside senior ML engineers and data scientists, you'll own experiments end to end – from data preparation through to model deployment in production.

What you'll do

• Build and evaluate ML models for time-series forecasting
• Prepare and validate training datasets from weather and grid data sources
• Deploy models to production using cloud ML infrastructure
• Monitor model performance and retrain on schedule
• Document experiments and results clearly for the research team

Qualifications

• Strong Python and experience with scikit-learn, XGBoost or PyTorch
• Comfortable with data wrangling using Pandas and NumPy
• Understanding of model evaluation and cross-validation
• Familiarity with version control for models and experiments (MLflow or similar)
• Good async written communication

Requirements

• Experience with time-series forecasting (nice to have)
• Familiarity with cloud ML platforms (SageMaker or Vertex AI) (nice to have)

Benefits

• $750–$1,200 USD/month, paid monthly
• Fully remote – work from anywhere
• Fully async – no fixed meeting schedule
• $500/year learning budget
• Home office equipment stipend