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Audio Machine Learning Intern Jobs in Austin, TX

Futran Tech Solutions Pvt. Ltd.

Big Data Developer

Austin, TX · On-site

$52.50 - $68.25/hr

... audio, and images. Relational databases and NoSQL databases, such as Apache Hadoop, Apache Spark ... Experience with machine learning algorithms and automated machine learning to automate and build ...

Base Power Company

Quantitative Developer Intern

Austin, TX · On-site

$19 - $25/hr

As an intern, you'll work on high-impact problems critical to Base's success and deliver solutions ... Proficiency in statistics, machine learning, and data-driven decision-making. * Strong software ...

Apple

Applied Scientist

Austin, TX · On-site

... audio, world-class workouts and meditations, super fun games and more! The Services Data Science ... machine learning to help optimize marketing channels, via observational testing frameworks ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/yr

... audio, world-class workouts and meditations, super fun games and more! The Services Data Science ... machine learning to help optimize marketing channels, via observational testing frameworks ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/yr

... audio, world-class workouts and meditations, super fun games and more! The Services Data Science ... machine learning to help optimize marketing channels, via observational testing frameworks ...

Cook & Boardman

Lead Audio Video Technician

Austin, TX · On-site

Career Growth: You'll benefit from continuous learning, mentorship, and leadership training ... These may include outdoor weather, proximity to forklifts or other heavy machinery, and the use of ...

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All JobsAudio Machine Learning Intern JobsAudio Machine Learning Intern Jobs in Austin, TX

Audio Machine Learning Intern information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

How much do audio machine learning intern jobs pay per year?

As of Jul 20, 2026, the average yearly pay for audio machine learning intern in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What does an Audio Machine Learning Intern do?

An Audio Machine Learning Intern assists in developing and improving machine learning models that process and analyze audio data. Their tasks may include data preprocessing, feature extraction, model training, and evaluation for applications like speech recognition, sound classification, or music analysis. Interns often collaborate with engineers and researchers to experiment with new algorithms and optimize audio-based AI systems. This role provides hands-on experience in both audio signal processing and machine learning techniques.

What types of projects can an Audio Machine Learning Intern expect to work on during their internship?

As an Audio Machine Learning Intern, you can expect to be involved in projects such as developing and fine-tuning audio classification models, working on speech recognition algorithms, or improving the accuracy of sound event detection systems. You may also assist with the collection and preprocessing of audio datasets, as well as support model evaluation and optimization. Collaboration with data scientists, audio engineers, and software developers is common, offering a hands-on learning environment and exposure to end-to-end machine learning workflows in the audio domain.

What are the key skills and qualifications needed to thrive as an Audio Machine Learning Intern, and why are they important?

To thrive as an Audio Machine Learning Intern, you need a solid background in signal processing, machine learning fundamentals, and programming skills, often supported by coursework or research in computer science or electrical engineering. Familiarity with Python, TensorFlow or PyTorch, and audio processing libraries like Librosa is typically required. Creativity, problem-solving abilities, and strong collaboration skills help you stand out in this role. These skills are crucial for developing innovative audio solutions, interpreting complex data, and working effectively within research or product teams.

What is the difference between Audio Machine Learning Intern vs Audio Data Analyst?

AspectAudio Machine Learning InternAudio Data Analyst
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fieldsDegree in Data Analysis, Statistics, or related fields; may have certifications in data tools
Work EnvironmentResearch labs, tech companies, or startups focusing on AI and audio techData-driven departments within media, entertainment, or tech companies
Employer & Industry UsageUsed in AI development, research projects, and product innovationUsed for analyzing audio data, improving user experience, and reporting

The Audio Machine Learning Intern focuses on developing models and algorithms for audio data, often in research or development settings. In contrast, the Audio Data Analyst primarily interprets audio data to generate insights and support decision-making. Both roles require familiarity with audio data, but the intern role emphasizes machine learning skills, while the analyst role centers on data analysis and reporting.

What are popular job titles related to Audio Machine Learning Intern jobs in Austin, TX? For Audio Machine Learning Intern jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning Intern jobs in Austin, TX look for? The top searched job categories for Audio Machine Learning Intern jobs in Austin, TX are:
What cities near Austin, TX are hiring for Audio Machine Learning Intern jobs? Cities near Austin, TX with the most Audio Machine Learning Intern job openings:
Audio Machine Learning Intern jobs near you

Big Data Developer

Futran Tech Solutions Pvt. Ltd.

Austin, TX • On-site

$52.50 - $68.25/hr

Full-time

Re-posted 3 days ago

Job description

Big Data Developer
Austin, TX (Day 1 onsite) - Full-time
Primary Skillset: Spark, Scala, AWS
Secondary Skillset : Python, Kafka
Job Description:
Common data archetypes, writing and coding functions, algorithms, logic development, control flow, object-oriented programming languages, external libraries and how to collect data from different sources.
This includes having knowledge of scraping, application program interfaces, databases, and publicly available repositories.
Structured data, such as from relational database management systems, and spreadsheets; semi structured data, such as log files, Extensible Markup Language and JavaScript Object Notation; and unstructured data, such as text, video, audio, and images.
Relational databases and NoSQL databases, such as Apache Hadoop, Apache Spark and other MPP databases.
SQL-based querying of databases using joins, aggregations, and subqueries.
Open-source tools, including real-time data processing products, such as Apache Beam, Kafka, and Spark Structured Streaming; time series databases, such as Influx DB; relational databases, such as Postgres; graph databases, such as Neo4j; and software development environments, such as Git and GitHub.
Abstraction tools, such as Kubernetes.
Mastery of computer programming and scripting languages, such as Scala, Java or Python, as well as an ability to create programming and processing logic.
Experience with machine learning algorithms and automated machine learning to automate and build continuous learning data processing streams and pipelines.
Data warehousing tools and techniques, such as Apache Hive.
Knowledge of cloud platform particularly AWS is also needed.

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