Algorithm & Machine Learning Intern

Job description

ENGIE Storage (formerly Green Charge) helps power the world more efficiently and sustainably. As the nation’s number one distributed energy storage company, we serve energy producers, distributors, and consumers, including utilities, network operators, and energy consumers in business and government.

Energy storage is a key enabler of a more sustainable energy future. At ENGIE Storage, you can help build this future by contributing to the development and deployment of GridSynergy®, a comprehensive, software-driven, field-proven battery-based energy storage system.

As the energy storage arm of ENGIE North America, we benefit from the stability and resources of a global energy company committed to addressing the major challenges of transitioning to a low-carbon energy system. With 154,950 employees in more than 70 countries, ENGIE achieved revenue of €69.9 billion in 2015.

We are looking for talented and motivated people to create the future of energy. Join a rewarding and flexible work environment that encourages innovation and creativity

The Role: Algorithm & Machine Learning Intern
Purpose
The Algorithm & Machine Learning Intern will assist in the development and testing of algorithms to generate new revenue streams and improve performance of existing revenue streams.

Reports to
Staff Algorithms Engineer

Location/Department
Santa Clara, CA / ENGIE Storage

Vacancy Status
Local Contract Only

Status
Salaried – Non -Exempt

Essential Job Functions

·  Analyze operational ESS data to identify/understand areas of improvement of the algorithms behind the ESS operations
·  Prototype algorithms from scratch for new ESS applications
·  Simulate operations of algorithms under development
·  Assist in designing, developing and deploying machine learning algorithms for Energy Storage Systems applications such as time series forecasting
·  Assist in modeling and simulating algorithms to evaluate performance before deploying to production
·  Assist in developing algorithms that use historical site data to identify potential system performance-impacting issues
·  Carries other duties as assigned

 

Requirements

·  Recent completion of advanced degree in Computer Science or related discipline
·  Some understanding of ML algorithms (time series analysis, probabilistic models, supervised classification and unsupervised learning), and applications.
·  Proficient in Python or R
·  Hands-on experience with ML libraries such as scikit-learn/keras/tensorflow etc..
·  Strong problem-solving skills and attention to detail
·  A portfolio of projects (GitHub, papers, etc.) is a plus
·  Smart, motivated, can do attitude and seeks to make a difference
·  Familiarity with Software Change, Configuration Management and Build Processes in a complex environment
Essential Physical Abilities

·  Ability to meet highest attendance requirements
·  Ability to communicate effectively, both written and verbally.
·  Ability to handle multiple assignments on a timely basis with a high degree of accuracy.
·  Ability to use personal computer, calculator, etc.
·  Could involve some lifting.
Education/Experience

·  MS or Ph.D. in Computer Science, Statistics, or equivalent field required   

 

Working Environment
Work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is not exposed to weather conditions. The noise level in the work environment is usually moderate.

 

For this role you must have authorization to work in the United States. Qualified applicants are considered for employment, and employees are treated during employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, gender identity, or expression, genetic information or any other legally protected status.

 

This job advertisement is supported by the ENGIE Talent Acquisition team. Agency involvement is not required. All related inquires must be done to the Talent Acquisition team, not direct to ENGIE North America Managers.

 

Additional Information
·  Posting Date: Apr 7, 2019