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Data Annotation Engineer Jobs in Reno, NV (NOW HIRING)

Data Annotation Engineer information

See Reno, NV salary details

$51.3K

$147K

$196.4K

How much do data annotation engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for data annotation engineer in Reno, NV is $147,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,800.00 and $195,400.00 per year, depending on experience, location, and employer.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What are the key skills and qualifications needed to thrive as a data annotation engineer?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Reno, NV? For Data Annotation Engineer jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Reno, NV look for? The top searched job categories for Data Annotation Engineer jobs in Reno, NV are:
What cities near Reno, NV are hiring for Data Annotation Engineer jobs? Cities near Reno, NV with the most Data Annotation Engineer job openings:
Infographic showing various Data Annotation Engineer job openings in Reno, NV as of July 2026, with employment types broken down into 68% Full Time, 14% Part Time, and 18% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $147,029 per year, or $70.7 per hour.

Software Engineer - ML/Computer Vision (Battery Sorting)

Redwood Materials

Mccarran, NV

Other

Re-posted 13 days ago


Redwood Materials rating

7.6

Company rating: 7.6 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

22nd of 89 rated recycling and waste


Job description

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

What Redwood Materials employees say

Pay

Hours and flexibility

Workplace

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