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Sign up with Clera and we'll reach out the moment a role actually fits you — no more spraying applications into the void.
$153k–$288k/yr
Full-time
bachelor degree
Posted 4d ago
~40 hrs/week
Responsibilities
Develop and maintain production software and ML models for an automated battery sorting platform. This includes managing the full pipeline from image acquisition and inference to integration with industrial control systems.
Requirements
Requires a degree in Computer Science or Electrical Engineering with 2+ years of industry experience in machine learning and computer vision. Candidates should be proficient in PyTorch and OpenCV and have experience deploying models in resource-constrained environments.
Full job description
About Redwood Materials
Redwood is localizing a global battery supply chain that seamlessly integrates recovery, reuse, and recycling — keeping critical minerals in circulation and driving the energy transition. Founded in 2017, we’re delivering low-cost and large-scale energy storage and producing battery materials in the U.S. for the first time, all from batteries we already have.
The Battery Sorting team at Redwood Materials is building a world-class, ML-enabled sorting platform that uses computer vision and machine learning to classify and route thousands of end-of-life batteries per hour across diverse chemistries and form factors. This role sits at the intersection of software engineering and machine learning, with direct ownership of the production systems powering automated battery sorting on the factory floor. The ideal candidate is equally comfortable debugging a production incident as iterating on a model, and will have the opportunity to generate patents in automated battery classification. This is a high-impact, highly visible role with immediate real-world application in advancing the energy transition.
Hours
Full-time | Schedule may vary depending on site operational needs; flexibility required
Responsibilities will include:
Develop, test, and maintain production software systems powering automated battery sorting, spanning ML inference, image acquisition, sensor integration, and hardware-adjacent control interfaces
Train and deploy computer vision models for battery chemistry classification, including dataset annotation, preprocessing, and evaluation within established data pipelines
Build and maintain services and APIs that connect ML outputs to downstream systems including MES, HMI, and PLC/controls interfaces
Own observability across the production software stack through structured logging, metrics dashboards, alerting, and on-call triage for inference pipelines and supporting services
Monitor model performance in production to catch regressions or distribution shifts and drive iterative improvements through data analysis and retraining
Contribute to infrastructure-as-code and CI/CD workflows to validate, version, and deploy application code and ML model artifacts to production environments
Collaborate cross-functionally with Controls, Hardware, Manufacturing, DevOps, and IT teams to translate operational needs into software and model improvements
Desired Qualifications:
B.S. in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience
2+ years of industry experience working with machine learning models, preferably in computer vision
Hands-on experience with ML frameworks and libraries such as PyTorch and OpenCV
Experience contributing to production codebases and pipelines with an emphasis on clean, well-documented, and well-tested code
Experience designing and tracking ML experiments using tools such as MLflow
Familiarity with edge deployment or model optimization techniques for inference (e.g., quantization, TensorRT, ONNX Runtime) in latency-sensitive or resource-constrained environments
Experience with OCR, image classification pipelines, or multi-sensor and multimodal fusion
Experience working in or alongside industrial, manufacturing, or operations environments where software interacts with physical systems
Strong cross-functional communication skills and ability to prioritize and execute in a fast-paced, dynamic environment
A passion for sustainability and making the world a better place!
Working Conditions:
Factory floor environment; work schedule may vary depending on site operational needs and flexibility is required
Willingness and ability to travel to Reno, NV as needed
Additional working conditions to be confirmed with Hiring Manager
In accordance with California pay transparency laws, the salary range for this position is listed below. Actual compensation may vary based on a variety of factors, including experience, education, and skills.
California Pay Range:
$152,500—$287,500 USD
The position is full-time. Compensation will be commensurate with experience.
We collect personal information (PI) from you in connection with your application for employment with Redwood Materials, including the following categories of PI: identifiers, personal records, professional or employment information, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment. If you have additional privacy-related questions, please contact us at [email protected].
Securing U.S. critical minerals. Powering America’s energy future.
Industry
Renewable Energy Equipment Manufacturing
Company size
1,001-5,000 employees
Headquarters
Carson City, Nevada
LinkedIn followers
80,896
Total funding
$4.2B
Redwood Materials is building the U.S. stockpile of critical materials and deploying large-scale energy storage. Founded by JB Straubel, the company produces lithium, nickel, cobalt, copper, and cathode active material at scale in the U.S., manufactures key components for advanced batteries, and deploys energy storage systems that power data centers and the nation’s grid. Redwood is expanding domestic capacity for next-generation energy storage and strengthening U.S. energy dominance.
Offices: 2800 Lockheed Way, Carson City, Nevada 89706, US
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