Machine Learning Software Engineer

Camuse Energy

Remote

Full Time

Posted May 9, 2026

$180k - $230k

Energy Management

Remote

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Job Description

A Machine Learning Engineer role focused on developing and deploying forecasting and predictive models for grid interconnection and energy management, working closely with cross-functional teams to translate data into actionable insights in the clean energy sector.

Key Responsibilities

Design, train, and evaluate predictive ML models for forecasting and time-series applications
Conduct exploratory data analysis, feature engineering, and statistical modeling on large datasets
Collaborate with engineering to deploy and integrate ML models into operational workflows
Work with teams to define problem statements and translate business objectives into ML solutions
Communicate model performance, uncertainty, and limitations to technical and non-technical audiences
Implement ML best practices around reproducibility, versioning, and testing

Requirements

PhD with 3 years of industry experience, Masters with 5 years, or Bachelors with 8 years in Machine Learning, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
Demonstrated track record of delivering ML models into production environments
Experience with time-series forecasting methods including classical approaches e.g. ARIMA and modern ML-based methods e.g. gradient boosting or temporal neural networks
Strong proficiency in Python and core ML data science libraries such as PyTorch, scikit-learn, statsmodels, pandas, etc.
Experience with probabilistic forecasting, uncertainty quantification, and backtesting
Ability to translate ambiguous business problems into well-scoped ML projects
Comfortable operating with autonomy in a small team, balancing speed of delivery with the engineering discipline that production-grade software demands