Software Engineer - ML/Computer Vision (Battery Sorting)
McCarran, NV; San Francisco, California, United States
- Pay
USD 152,500–200,000/yearAnnual period assumed — pay source
California Pay Range: $152,500—$200,000 USD The position is full-time. Compensation will be commensurate with experience.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
$152,500—$200,000 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 privacy@redwoodmaterials.com.
Read the full posting
What you’ll work on
Full postingDevelop and maintain production software for automated battery sorting
Train and deploy computer vision models for battery chemistry classification
Build services and APIs connecting ML outputs to MES, HMI, and PLC systems
Own observability, alerting, and on-call triage for inference pipelines
Monitor production models for regressions and drive retraining
From the employer’s posting
Develop, test, and maintain production software systems powering automated battery sorting
Train and deploy computer vision models for battery chemistry classification
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
What you’ll bring
All qualificationsPreferred 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
Qualification wording
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
Tools in this posting
- MLflow
- PyTorch
Source — Tool mentions in context
- 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
- 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
About Redwood Materials
Redwood Materials was founded in 2017 by JB Straubel, co-founder and former CTO of Tesla, on a simple but radical idea: the critical minerals powering the energy transition already exist.
In the employer’s words · Read in context
Posting record
Report an errorOpen 4 monthsWe first saw this posting 127 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 25, 2026 · 127 days ago
- Recorded sightings
- 148
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
About Redwood Materials
Redwood Materials was founded in 2017 by JB Straubel, co-founder and former CTO of Tesla, on a simple but radical idea: the critical minerals powering the energy transition already exist. They just need to come back. Today Redwood is the largest lithium-ion battery recycler in North America — recovering, refining, and redeploying critical minerals from end-of-life batteries back into the supply chain. On the energy side, Redwood has deployed the largest second-life battery project in the world, delivering power to AI data centers in months rather than years using proprietary energy architecture engineered entirely in-house. The company is profitable, the market it operates in is projected to grow 20 to 50 times over the next decade, and Redwood is the only company with the supply chain, the technology, and the operational scale to lead it.
Software Engineer, ML/Computer Vision (Battery Sorting)
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.
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 privacy@redwoodmaterials.com.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
California Pay Range: $152,500—$200,000 USD The position is full-time. Compensation will be commensurate with experience.
- Location & working pattern
McCarran, NV; San Francisco, California, United States
Hours Full-time | Schedule may vary depending on site operational needs; flexibility required Responsibilities will include:
More source context
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
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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