1

Audio Machine Learning Intern Jobs in Piscataway, NJ

Showing results 41-60

Audio Machine Learning Intern information

See Piscataway, NJ salary details

$26K

$43.4K

$89.7K

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

As of Aug 20, 2026, the average yearly pay for audio machine learning intern in Piscataway, NJ is $43,388.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,100.00 and $46,900.00 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 Piscataway, NJ?

For Audio Machine Learning Intern jobs in Piscataway, NJ, the most frequently searched job titles are:

What cities near Piscataway, NJ are hiring for Audio Machine Learning Intern jobs?

Cities near Piscataway, NJ with the most Audio Machine Learning Intern job openings:

Infographic showing various Audio Machine Learning Intern job openings in Piscataway, NJ as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 4% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $43,388 per year, or $20.9 per hour.

Senior Machine Learning Engineer - Enrichment & Content Intelligence

Spotify

New York, NY โ€ข On-site

$184K - $262K/yr

Full-time

Medical, Retirement, PTO

Re-posted 24 days ago


Job description

The Experience team designs Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

The Enrichment & Content Intelligence team sits within Content Platform in the Experience Mission. We build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale. Our systems help answer foundational questions across the platform: which tracks are the same recording, which music videos match which audio tracks, who wrote and performed a song, and how content relationships connect across Spotify's catalog.

Our infrastructure powers products and experiences used by millions of listeners, artists, and creators every day. From recommendations and charts to royalties and artist tooling, the work we do directly shapes how content is understood and surfaced across Spotify.

We're looking for a Senior Machine Learning Engineer to help evolve the machine learning systems behind Recording Groups, Music Video Resolution, SongDNA, and the Music Knowledge Graph. This role sits at the intersection of multimodal machine learning, entity resolution, and production-scale engineering, with opportunities to work across audio, video, and metadata understanding problems at massive scale.

What You'll Do
  • Own and evolve large-scale ML pipelines powering Spotify's content-resolution systems
  • Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA
  • Improve entity-resolution systems across music and video content, helping Spotify better understand relationships between recordings, versions, and content formats
  • Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis
  • Build scalable ML evaluation and monitoring infrastructure, including standardized datasets, retraining workflows, and continuous improvement systems
  • Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management
  • Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission
  • Help shape technical strategy for the squad and contribute to long-term ML direction across the product area
  • Mentor engineers and contribute to a strong culture of technical collaboration and experimentation
Who You Are
  • You have solid experience building, deploying, and maintaining machine learning systems in production at scale
  • You have strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow
  • You have experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains
  • You understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities
  • You know how to design evaluation systems that balance model quality, operational performance, and real-world impact
  • You are experienced working with large-scale distributed data processing systems and ML infrastructure
  • You communicate effectively across engineering, product, and data science stakeholders
  • You are comfortable leading technical initiatives and influencing engineering direction within a team
  • Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks is a plus
  • Experience with Scala is a plus
  • Experience with computer vision, video understanding, multimodal embeddings, or recommendation systems is a strong plus
Where You'll Be
  • This role is based in New York City
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
The United States base range for this position is $184,049-262,928 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
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. Find our AI notice here: https://lifeatspotify.com/ai-notice
apply for this job