ZipRecruiter

Log In

1

Audio Machine Learning Intern Jobs in Berkeley, CA

Bland

Machine Learning Researcher, Audio

San Francisco, CA · On-site

$140K - $250K/yr

Machine Learning Researcher, Audio Location: San Francisco, CA or Remote About Bland At Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco, we ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

Design, develop, and deploy deep-learning-based and classical DSP audio algorithms for our SPU ... Desired Skills and Experience Deep learning, Machine learning, DSP, Python, PyTorch Benefits ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

next page

Showing results 1-20

All JobsAudio Machine Learning Intern JobsAudio Machine Learning Intern Jobs in Berkeley, CA

Audio Machine Learning Intern information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

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

As of Jul 5, 2026, the average yearly pay for audio machine learning intern in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 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 job categories do people searching Audio Machine Learning Intern jobs in Berkeley, CA look for? The top searched job categories for Audio Machine Learning Intern jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Audio Machine Learning Intern jobs? Cities near Berkeley, CA with the most Audio Machine Learning Intern job openings:
Audio Machine Learning Intern jobs near you

Machine Learning Intern

Droyd Robotics

San Francisco, CA • On-site

Internship

Posted 13 days ago

Job description

About the team
Droyd builds autonomous robotic systems that automate repetitive manual work in real environments. Our robots operate under tight compute, latency, and reliability constraints, so learning systems must work cleanly on real hardware.
Our AI team builds the models and inference systems that let robotic arms see, reason, and act. This work runs on deployed robots, not demos.
About the role
As a Machine Learning Intern at Droyd, you'll work directly on the learning and inference systems that power our robotic arms. You'll train models, run experiments, and help push research into production.
You'll work closely with AI researchers, software engineers, and hardware teams, and contribute to systems that ship to real robots.
This role is based in San Francisco, CA. We're an in-person company. We build faster that way.
In this role, you'll
  • Work across the ML stack, from training to inference
  • Train and evaluate models that run on low-payload robotic systems
  • Run experiments, analyze results, and document findings
  • Learn how model design, data quality, and hardware constraints affect real-world performance
  • Support deployment and testing of models on robotic hardware
We're looking for candidates who
  • Are current juniors or seniors (or equivalent) studying computer science, machine learning, AI, or a related field
  • Have coursework or hands-on experience training ML models using frameworks like PyTorch or JAX
  • Are willing to balance school and work in a fast-moving environment
  • Are curious about robotics and interested in how learning systems behave in the real world
  • Take ownership, ask good questions, and can carry projects forward with guidance
About Droyd
Droyd builds autonomous robotic systems to automate manual work for enterprises. We design the hardware, collect our own data, and train models that operate under real-world constraints.
If we do this right, robots become dependable tools people rely on every day.
Join us and help build systems that ship.

Apply