Remote ML Engineer — Time-Series Forecasting

Camus Energy; Campbell (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Fully remote

Bay Area in-office option

Flexible PTO

Impact on climate

Job summary

Camus Energy in Campbell, CA is seeking a Machine Learning Engineer to own forecasting and predictive modeling at the heart of the platform. This individual contributor role covers the full lifecycle from exploratory analysis and model design through to production deployment and monitoring.

You will work closely with Camus’ teams and external stakeholders to translate messy real‑world signals into reliable analytics and to integrate ML models into planning and operations, shaping product

Qualifications

• 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)

Responsibilities

• Design, train, and evaluate predictive ML models with a focus on forecasting and time-series applications
• 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

Skills

Python

PyTorch

Scikit-learn

Time-series forecasting

Data analysis

ML production

Uncertainty quantification

Communication

Education

PhD in related field

Masters in related field

Bachelors in related field

Tools

Airflow

Spark

Databricks

Docker

Kubernetes

Job description

Camus Energy in Campbell, CA is seeking a Machine Learning Engineer to own forecasting and predictive modeling at the heart of the platform. This individual contributor role covers the full lifecycle from exploratory analysis and model design through to production deployment and monitoring.

You will work closely with Camus’ teams and external stakeholders to translate messy real‑world signals into reliable analytics and to integrate ML models into planning and operations, shaping product