Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
Quick apply
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...
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Quick apply
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Audio Machine Learning information
See California salary details
$29.1K - $41.9K
16% of jobs
$47.7K is the 25th percentile. Wages below this are outliers.
$41.9K - $54.6K
19% of jobs
$54.6K - $67.3K
13% of jobs
The median wage is $68.8K / yr.
$67.3K - $80.1K
14% of jobs
$80.1K - $92.8K
10% of jobs
$98.7K is the 75th percentile. Wages above this are outliers.
$92.8K - $105.6K
6% of jobs
$105.6K - $118.3K
4% of jobs
$118.3K - $131K
5% of jobs
$131K - $143.8K
4% of jobs
$143.8K - $156.5K
8% of jobs
$156.5K - $169.3K
0% of jobs
$29.1K
$83.3K
$169.3K
How much do audio machine learning jobs pay per year?
As of Jun 7, 2026, the average yearly pay for audio machine learning in California is $83,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,300.00 and $111,500.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?
To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.
What are the typical daily responsibilities of someone working in Audio Machine Learning?
Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.
What is an Audio Machine Learning job?
An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.
What are the most commonly searched types of Audio Machine Learning jobs in California? The most popular types of Audio Machine Learning jobs in California are:
What are popular job titles related to Audio Machine Learning jobs in California? For Audio Machine Learning jobs in California, the most frequently searched job titles are:
- Internship Edge Ai Machine Learning
- Cnn Com
- Machine Learning Engineer Biotech
- Remote Prototype Machinist
- Applied Scientist Machine Learning
- Entry Level Machine Learning Engineer
- Flexible Remote Machine Learning Engineer
- Google Cloud Machine Learning Engineer
- Freelance Machine Learning Data Annotation
- Machine Learning Engineer
What job categories do people searching Audio Machine Learning jobs in California look for? The top searched job categories for Audio Machine Learning jobs in California are:
What cities in California are hiring for Audio Machine Learning jobs? Cities in California with the most Audio Machine Learning job openings:
Job description
Summary Description:
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey Gobble Synthesis.
Syntiant Corp. is seeking a turkey gobble detector AED model that runs on NDP chips. It is difficult to collect good quality gobble data due to several logistical issues. As of now, only ~2K samples are available for training such a model. These samples are not enough to train a production quality turkey gobble model.
EcoGen is a neural network model that could generate synthetic but real-sounding bird sounds. It needs only a handful of recordings to synthesize similar sounds. The idea is to leverage this model to get more data for training a better turkey gobble detector AEDmodel. For details on EcoGen, please refer to the hyperlink provided. There are newer models such as BirdDiff, Audio LDM (Text-to-Turkey), Perch 2.0 etc.
Requirements
Specific Duties and Responsibilities:
- Understanding the model architecture.
- Running it locally or on the cluster.
- Fine-tuning the model on the available turkey sounds.
- Synthesizing real-sounding artificial turkey gobble sounds.
- Explore better alternatives and pursue them.
Qualifications, Education, and Experience Required:
- Candidate pursuing a Bachelor's or Master's degree in Computer Science or related field with hands-on experience in AI/ML model training.
- Industry work experience is not required, but it would be good to have.
Benefits
About Syntiant:
Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering hardware and software solutions for edge AI deployment. The company's purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions with proprietary model architectures that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world's leading strategic and financial investors including Intel Capital, Microsoft's M12, Applied Ventures, Bosch Ventures, the Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com.
About Syntiant
Sourced by ZipRecruiter
Company size
51 - 200 Employees
Headquarters location
Irvine, CA, US
Year founded
2017