Machine Learning Engineer (Data Pipelines)

Machine Learning Engineer (Data Pipelines)

**Remote with Occasional Travel to Los Angeles Area**

The Company

Our client is an exciting new startup that is making power more accessible and efficient through industry-leading portable energy storage paired with advanced predictive software. They will be supporting a wide variety of industries including manufacturing facilities, EV charging stations, data centers, and other critical infrastructure sites, by delivering mobile power directly to their customers’ locations.

The Job

Our client is seeking a Machine Learning Engineer (Data Pipelines) to help build the infrastructure and machine learning models needed for their mobile power systems to integrate seamlessly with the grid and efficiently manage power needs.

Functions

Design, maintain, and improve well-documented, production-ready Python packages for energy modeling and control

Collaborate with the engineering team to evolve our client’s control architecture and backend services

Develop integrations with DER devices using industrial protocols such as MODBUS and CAN

Build and deploy infrastructure using tools like Docker, Terraform, and Ansible

Translate utility tariffs and DER characteristics into code for analysis

Build AWS-based data pipelines for telemetry ingestion and historical analysis

Write clear and maintainable documentation, configuration interfaces, and internal tooling

Contribute to modeling physical, economic, and control behaviors of distributed assets

Learn and apply evolving standards and technologies such as UL 3141, IEEE 2030.5, or UL 9540

Apply state-of-the-art AI techniques to control, forecasting, or optimization problems and deploy them in real-world energy systems

Qualifications

Experience with AWS services and building scalable telemetry or control pipelines

Comfortable modeling and simulating real-world systems (e.g., batteries, tariffs, control loops)

Demonstrated ability to apply and deploy AI/ML models in real-life applications

Strong communication and collaboration skills, especially across disciplines

Ability to learn complex topics like grid interconnection standards and utility data systems

Proficiency in Python with experience maintaining production software and internal libraries

Preferred Skills

Master’s or PhD in Computer Science, Electrical Engineering, Physics, Mathematics, or a similar technical field

Strong grasp of electricity fundamentals and renewable energy technologies

Experience with infrastructure-as-code tools like Docker, Terraform, and Ansible

Familiarity with industrial communication protocols such as MODBUS and CAN