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Assistant Music Metadata Jobs in Raritan, NJ (NOW HIRING)

Company 3 / Method Inc.

Color Assist

New York, NY · On-site

$22 - $30/hr

... metadata. * Help support new processes and maintain proficiency with evolving technical ... Previous exposure to short form projects such as commercials, music videos, documentaries, or short ...

Company3

Color Assist

New York, NY · On-site

... metadata. * Help support new processes and maintain proficiency with evolving technical ... Previous exposure to short form projects such as commercials, music videos, documentaries, or short ...

All JobsMusic Metadata JobsAssistant Music Metadata JobsAssistant Music Metadata Jobs in Raritan, NJ

Assistant Music Metadata information

What does an assistant music metadata do?

An Assistant Music Metadata professional is responsible for organizing, entering, and maintaining accurate information about music tracks, albums, and artists in digital databases. Their work involves tagging songs with relevant details such as genre, release date, composer, and other identifiers to ensure that users can easily search and discover music. They often collaborate with record labels, streaming platforms, and other metadata teams to ensure consistency and accuracy across platforms. This role is vital for the proper categorization and discoverability of music in digital libraries.

What are the key skills and qualifications needed to thrive as an assistant music metadata, and why are they important?

To thrive as an Assistant Music Metadata, you need strong attention to detail, a solid understanding of music genres, and familiarity with cataloging or library science principles, often supported by a relevant degree or coursework. Proficiency with music metadata management systems, content management tools, and spreadsheet software like Excel is typically required. Excellent organizational skills, communication, and the ability to work collaboratively are important soft skills for this role. These skills ensure accurate, efficient organization and retrieval of music data, supporting discoverability and seamless user experiences on digital platforms.

What are some common challenges faced by an assistant music metadata specialist, and how can they be addressed?

Assistant Music Metadata specialists often encounter challenges such as ensuring the accuracy and consistency of large volumes of music data, staying updated on industry standards, and resolving discrepancies between various data sources. To address these, it's essential to develop a keen attention to detail, maintain thorough documentation, and proactively communicate with team members and content providers. Leveraging specialized metadata management tools and participating in regular training sessions can also help tackle these challenges effectively.

What is the difference between Assistant Music Metadata vs Assistant Music Licensing?

AspectAssistant Music MetadataAssistant Music Licensing
Primary RoleManaging and organizing music data, tags, and catalog informationHandling licensing agreements, rights clearance, and licensing negotiations
Required SkillsAttention to detail, knowledge of music databases, metadata standardsLegal knowledge, negotiation skills, understanding licensing laws
Work EnvironmentMusic libraries, digital databases, media companiesMusic publishers, licensing agencies, record labels
Common UsageEnsuring accurate music data for streaming and distributionSecuring rights for music use in media and public performances

While both roles support the music industry, Assistant Music Metadata focuses on organizing and maintaining accurate music data, whereas Assistant Music Licensing deals with securing legal rights for music use. Both positions require industry knowledge but serve different functions within the music ecosystem.

What cities near Raritan, NJ are hiring for Assistant Music Metadata jobs?

Cities near Raritan, NJ with the most Assistant Music Metadata job openings:

Assistant Music Metadata jobs near you

Senior Machine Learning Engineer - Enrichment & Content Intelligence

Spotify

New York, NY • On-site

$184K - $262K/yr

Full-time

Medical, Retirement, PTO

Re-posted 26 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
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