Job Description
Description
Position: Machine Learning Researcher (Full-time, Permanent)
Location: Newport Beach, CA (Onsite)
Salary: $150-185k
Benefits:
+ Employer-subsidized health, dental, and vision benefits
+ Flexible (Unlimited) Time Off
+ Paid parental leave
+ Paid holidays
+ 401k options with 100% match
Overview:
We are seeking a Machine Learning Researcher to work with one of our clients based in Newport Beach, CA.
Our client builds gigawatt scale campuses for datacenter customers, co-located with battery energy storage and solar generation. As the Machine Learning Engineer, you will be responsible for developing forecasting models and optimization routines to maximize the value delivered to customers by efficiently orchestrating these resources.
The company is building gigawatt-scale campuses purpose-built for AI data centers, overseeing the full development and orchestration of power infrastructure, from grid interconnects to behind-the-meter solar and large-scale energy storage systems. With over 5 gigawatts of capacity in various stages of development, the projects currently under construction rank among the largest globally.
As AI drives exponential energy demand, balancing that need with scalable, clean energy solutions is one of the most critical challenges, and opportunities, of our time. The company we're working with is uniquely positioned at the center of this global transformation, helping to power the future of intelligent infrastructure.
Key Responsibilities:
+ Create forecast models for energy prices, datacenter load, and solar generation.
+ Discover and incorporate new data sources to improve model accuracy.
+ Develop algorithms for the optimal dispatch of battery energy storage systems.
+ Keep abreast of the latest advancements in machine learning (ML) research to identify innovative solutions for energy-related challenges.
+ Write, optimize, and review code with an emphasis on performance and readability.
+ Work collaboratively across the organization to maximize the value of forecasts and optimization efforts.
Requirements
Minimum Requirements:
-Master's degree in Mathematics, Machine Learning, Statistics, or relevant quantitative field of study (PhD preferred)
-Minimum of 1 year of relevant hands-on experience, to include:
+ Ability to write production quality code in Python
+ Familiarity with ML frameworks like TensorFlow or PyTorch.
+ Experience with a variety of forecasting algorithms and approaches from regression through to deep learning.
+ Demonstrate exceptional analytical and problem-solving abilities.
+ Exhibit strong mentorship, communication, and teamwork capabilities.
+ Ability to work independently and manage multiple projects simultaneously.
+ Show enthusiasm for continuous learning and a keen interest in the energy sector.
Preferred Requirements:
+ PhD in Mathematics, Machine Learning, Statistics, or relevant quantitative field of study
+ Domain expertise in forecasting and analysis of electricity markets such as ERCOT.
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Job Tags
Permanent employment, Full time, Contract work, Temporary work, Flexible hours,
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