Machine Learning Software Engineer

Camus Energy

United States

United States

About

Job Description: Design, train, and evaluate predictive ML models with a focus on forecasting and time-series applications Conduct exploratory data analysis, feature engineering, and statistical modeling across large structured and unstructured datasets Collaborate with Engineering to define ML infrastructure requirements, and deploy and integrate ML models into operational workflows and decision-support tools Work cross-functionally with Camus teams to define problem statements and translate business objectives into ML solutions Communicate model performance, uncertainty, and limitations clearly to both technical and non-technical audiences Champion 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 (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 xywuqvp operating with autonomy in a small team, balancing speed of delivery with the engineering discipline that production-grade software demands. Benefits:
Competitive base salary Comprehensive benefits, including FSA and 401k for full time employees Fully remote workplace with options for in office work in the Bay Area Flexible PTO, which we encourage you to use! A real impact on climate change - we’re building the world we want to live in and we want you to join us!

United States

Languages

English

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