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Machine Learning and Process Control Software Developer

Active

State & Local

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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This subcontract involves the development of specialized software and machine learning tools to support prime contractors on California Energy Commission battery manufacturing projects. The scope of work focuses on creating ML algorithms for analyzing electrode measurement data and designing software interfaces to enable real-time process control. Technical execution will utilize PyTorch, TensorFlow, and high-performance computing environments to deliver a comprehensive software suite and ML models intended for platform enhancement. The project is categorized under NAICS code 541511 and is associated with the California Energy Commission. It was posted on October 14, 2025, and is structured as a subcontract to provide critical technical capabilities for battery manufacturing innovation.

General Info

Subcontract for developing ML tools and software for California Energy Commission battery manufacturing.

Agency

California → Energy Commission

NAICS

541511 - Custom Computer Programming Services

Place of Performance

CA

Set-Aside

NONE

Documents

This scope was carved out of EPC-25-030.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Cold Atmospheric Plasma-Based Inspection & Real-Time Process Control of Electrode Materials to Enable High-Performance Battery Manufacturing

AI Contract Breakdown

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Timeline

PostedOct 14

subcontract

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Organization & Contact Information

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AgencyCalifornia → Energy Commission

ContactsNo contacts available

OfficeN/A

Organization / Agency

California → Energy Commission

Office AddressN/A

ContactsNo contact information available

Full Description

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Develops software and machine learning tools for prime contractors on California Energy Commission battery manufacturing projects. Creates ML algorithms for electrode measurement data analysis and software interfaces for real-time process control. Employs PyTorch, TensorFlow, and high-performance computing environments. Delivers a software suite and ML models for platform enhancement.

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