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Entry Level Audio Machine Learning Jobs (NOW HIRING)

FieldAI

3D Machine Learning Engineer

Irvine, CA

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ...

SynergisticIT

Machine Learning Engineer

Mount Pleasant, SC · On-site

$109K - $131K/yr

For entry-level candidates, practical proof matters. SynergisticIT is looking for candidates interested in ML/AI programming, Python, machine learning, NLP, model evaluation, APIs, data pipelines ...

Apple

Machine Learning Engineer, SIML

Cupertino, CA

$216K - $324K/yr

Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...

Apple

Machine Learning Engineer, SIML

Cupertino, CA

$216K - $324K/yr

Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...

Apple

Machine Learning Engineer, SIML

Cupertino, CA · On-site

Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...

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Entry Level Audio Machine Learning information

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How much do entry level audio machine learning jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for entry level audio machine learning in the United States is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $18.99 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Audio Machine Learning vs Entry Level Audio Signal Processing?

AspectEntry Level Audio Machine LearningEntry Level Audio Signal Processing
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Acoustics, or related; knowledge of DSP tools
Work EnvironmentTech companies, research labs, startups focusing on AI applications in audioAudio equipment manufacturers, telecommunications, research labs
Industry UsageDeveloping AI models for speech recognition, audio classification, sound analysisDesigning audio filters, signal enhancement, audio hardware integration

Entry Level Audio Machine Learning focuses on developing AI models for audio applications, requiring programming and ML skills. Entry Level Audio Signal Processing emphasizes traditional audio analysis and hardware integration, requiring DSP knowledge. Both roles are essential in the audio industry but differ in technical focus and tools used.

What are the most commonly searched types of Audio Machine Learning jobs? The most popular types of Audio Machine Learning jobs are:
What job categories do people searching Entry Level Audio Machine Learning jobs look for? The top searched job categories for Entry Level Audio Machine Learning jobs are:
Entry Level Audio Machine Learning jobs near you

3D Machine Learning Engineer

FieldAI

Irvine, CA

Other

Re-posted 28 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.
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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.
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