... audio, and Building Information Models (BIM). • Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
... audio, and Building Information Models (BIM). • Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
3D Machine Learning Engineer
Irvine, CA · On-site
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
3D Machine Learning Engineer
Irvine, CA · On-site
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
3D Machine Learning Engineer
Irvine, CA · On-site
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
Quick apply
3D Machine Learning Engineer
Irvine, CA · On-site
... audio, and Building Information Models (BIM). * Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and ...
Audio Annotation information
See Riverside, CA salary details
$30.8K - $44.2K
16% of jobs
$50.4K is the 25th percentile. Wages below this are outliers.
$44.2K - $57.7K
19% of jobs
$57.7K - $71.2K
13% of jobs
The median wage is $72.7K / yr.
$71.2K - $84.6K
14% of jobs
$84.6K - $98.1K
10% of jobs
$104.3K is the 75th percentile. Wages above this are outliers.
$98.1K - $111.6K
6% of jobs
$111.6K - $125.1K
4% of jobs
$125.1K - $138.5K
5% of jobs
$138.5K - $152K
4% of jobs
$152K - $165.5K
8% of jobs
$165.5K - $178.9K
0% of jobs
$30.8K
$88.1K
$178.9K
How much do audio annotation jobs pay per year?
As of Jul 8, 2026, the average yearly pay for audio annotation in Riverside, CA is $88,110.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,200.00 and $117,900.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as an Audio Annotator, and why are they important?
To thrive as an Audio Annotator, you need strong attention to detail, excellent listening skills, and familiarity with linguistic concepts, often supported by relevant coursework or experience in linguistics or audio processing. Proficiency in annotation tools such as ELAN, Audacity, or Praat, as well as experience with data labeling platforms, is typically required. Strong organizational skills, patience, and the ability to work independently make someone stand out in this role. These skills ensure accurate and consistent audio data labeling, which is essential for training reliable AI and speech recognition systems.
What are some common challenges faced by audio annotators, and how can they be managed effectively?
Audio annotators often encounter challenges such as distinguishing overlapping voices, dealing with low-quality recordings, and maintaining consistency in labeling. To manage these, it's important to use high-quality headphones, familiarize yourself with annotation guidelines, and communicate regularly with your team to resolve ambiguities. Many organizations also provide regular feedback sessions and quality checks to ensure accuracy and support continuous improvement.
What jobs make $3,000 a month without a degree?
Audio annotation jobs can pay around $3,000 per month for experienced workers, especially those working full-time or on high-volume projects. These roles typically require strong attention to detail, familiarity with audio editing tools, and the ability to work independently, often without formal degrees. Compensation varies based on experience, workload, and the platform or employer.
What is the salary of audio annotation?
The salary for audio annotation jobs typically ranges from $10 to $20 per hour, depending on experience, location, and the complexity of the tasks. Many positions are freelance or part-time, often requiring basic computer skills and attention to detail.
How to become an AI annotator?
To become an AI annotator, you typically need strong attention to detail, good listening skills, and basic computer proficiency. Many roles require familiarity with annotation tools and sometimes a high school diploma or equivalent. Gaining experience through online training or tutorials can improve your chances of securing a position in this field.
What is audio annotation?
Audio annotation is the process of labeling or tagging audio data with relevant information, such as identifying sounds, speech, speakers, or background noises. This process helps train machine learning models to recognize and understand audio content. Audio annotation can involve tasks like transcribing speech, marking segments with specific sounds, or categorizing audio clips by genre or emotion. It is widely used in developing applications for speech recognition, virtual assistants, and audio analysis.
What is an audio annotation job?
An audio annotation job involves listening to audio recordings and labeling or transcribing specific sounds, speech, or events to create datasets used for training machine learning models. Workers typically use specialized tools and need good listening skills, attention to detail, and sometimes basic knowledge of audio editing or annotation software.
What are popular job titles related to Audio Annotation jobs in Riverside, CA? For Audio Annotation jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Audio Annotation jobs in Riverside, CA look for? The top searched job categories for Audio Annotation jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Audio Annotation jobs? Cities near Riverside, CA with the most Audio Annotation job openings:
Full-time
Posted 26 days ago
Job description
Job Summary:
FieldAI is a company based in Irvine, California, specializing in embodied AI and robotics. They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking and scene understanding in construction environments.
Responsibilities:
• Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding.
• Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud platforms such as AWS (e.g., SageMaker, EC2).
• Collaborate with software and systems engineers to integrate models into production environments and continuously improve inference pipelines.
• Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM).
• Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, or a related technical field.
• 2+ years of hands-on industry experience developing and deploying machine learning systems for 3D point clouds, perception, or spatial understanding tasks.
• Strong background in 3D machine learning, with experience in deep learning for point clouds, multi-view fusion, or geometric learning.
• Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.
• Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data preprocessing.
• Experience training, evaluating, and deploying ML models using cloud infrastructure (e.g., AWS, SageMaker) and containerized workflows.
• Solid understanding of the end-to-end ML lifecycle, including experiment tracking, reproducibility, model versioning, and optimization for production.
• Proven ability to work in fast-paced, interdisciplinary teams across software, ML, and product teams.
Preferred:
• Experience working with BIM data, digital twins, or construction-related sensor data.
• Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene representations.
• Familiar with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
• Strong foundation in geometric computer vision, robotics, or algorithmic 3D reasoning.
• Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF, Occupancy Networks).
• Deep experience with point cloud and graph learning frameworks such as Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
• Experience building custom modules for SparseConvNet or 3D transformers.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.
FieldAI is a company based in Irvine, California, specializing in embodied AI and robotics. They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking and scene understanding in construction environments.
Responsibilities:
• Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding.
• Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud platforms such as AWS (e.g., SageMaker, EC2).
• Collaborate with software and systems engineers to integrate models into production environments and continuously improve inference pipelines.
• Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM).
• Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, or a related technical field.
• 2+ years of hands-on industry experience developing and deploying machine learning systems for 3D point clouds, perception, or spatial understanding tasks.
• Strong background in 3D machine learning, with experience in deep learning for point clouds, multi-view fusion, or geometric learning.
• Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.
• Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data preprocessing.
• Experience training, evaluating, and deploying ML models using cloud infrastructure (e.g., AWS, SageMaker) and containerized workflows.
• Solid understanding of the end-to-end ML lifecycle, including experiment tracking, reproducibility, model versioning, and optimization for production.
• Proven ability to work in fast-paced, interdisciplinary teams across software, ML, and product teams.
Preferred:
• Experience working with BIM data, digital twins, or construction-related sensor data.
• Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene representations.
• Familiar with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
• Strong foundation in geometric computer vision, robotics, or algorithmic 3D reasoning.
• Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF, Occupancy Networks).
• Deep experience with point cloud and graph learning frameworks such as Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
• Experience building custom modules for SparseConvNet or 3D transformers.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.