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Audio Annotation Jobs in Riverside, CA (NOW HIRING)

... 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 ...

Audio Annotation information

See Riverside, CA salary details

$30.8K

$88.1K

$178.9K

How much do audio annotation jobs pay per year?

As of May 31, 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 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 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:

3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Full-time

Posted 18 days ago


Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
As a 3D Machine Learning Engineer, you will focus on designing, implementing, training, and maintaining cutting-edge 3D and multimodal machine learning models that process reality capture data such as 3D point clouds, 360 photos, and RGBD images. Your work will directly contribute to automated progress tracking, deviation analysis, and semantic scene understanding of construction sites. You will collaborate closely with software, autonomy, and product teams to ensure seamless integration of these AI models into our production environments.
What You'll Do
  • 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.

What You Have
  • 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.

The Extras That Set You Apart
  • 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.

Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.
Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.
Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.
We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.