Job Description
A senior engineer role focused on scaling and improving the reliability of data infrastructure to support large-scale machine learning models for energy price forecasting and climate impact mitigation at a startup using deep learning and data-driven energy solutions.
Key Responsibilities
- Lead the scaling and reliability of the company's data infrastructure.
- Scale data ingestion to incorporate petabyte-scale weather data and increase spatial granularity for ML models.
- Improve the reliability of data pipelines by addressing issues such as downtime, late-arriving data, and changing schemas.
Requirements
- Experience in scaling and improving the reliability of data infrastructure, including data pipelines and platforms.
- Ability to scale data usage in machine learning models by a factor of 10-100x, incorporating petabyte-scale weather data and increasing spatial granularity of price forecasting.
- Proficiency in addressing real-world data ingestion problems such as downtime, late-arriving data, and changing schemas.
- Experience with data pipeline reliability improvements to support large-scale data processing for machine learning applications.
- Strong understanding of data engineering principles, including data ingestion, processing, and storage at scale.
- Experience working with external data sources and managing data quality issues.
- Ability to work collaboratively in a hybrid work environment, with in-person presence required 3 days a week at the Cupertino office.
Benefits & Perks
Hybrid work policy requiring 3 days per week in the Cupertino office
Opportunity to work on complex real-world problems related to energy and climate
Involvement in large-scale data challenges and ML applications
Potential for career growth through technical interviews and on-site panels
Ready to Apply?
Join Gridmatic and make an impact
Stay Updated on Sustainability Jobs
Get the latest renewable energy jobs and career tips delivered to your inbox.
Job Alerts
Get notified about new sustainability jobs