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Audio Annotation Jobs in Newark, NJ (NOW HIRING)

Neonmoneytalks

Data Ops Lead

Manhattan, NY · On-site

$100 - $140/hr

About the role Your mission is to turn Neon's raw consumer audio streams into the cleanest, most ... Standing up human transcription, annotation and other operations, largely overseas, that make it ...

New

Neon Mobile, Inc

Data Ops Lead

New York, NY · On-site +1

$160K - $220K/yr

About the role Your mission is to turn Neon's raw consumer audio streams into the cleanest, most ... Standing up human transcription, annotation and other operations, largely overseas, that make it ...

Welo Data

Data Labeling Associate

New York, NY

$34/hr

Execute Data labelling and annotation tasks across speech and voice datasets. * Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A FIT IF YOU'RE... * A ...

Welocalize

Polish Data Labeler

New York, NY

$26 - $28/hr

Execute high-volume data labeling and annotation tasks across speech and voice datasets * Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale * Work with audio and ...

YO AI Labs

Japanese Language Expert - Remote

New York, NY · Remote

$24 - $31.75/hr

In this role, you will work with Japanese and English audio and written content, ensuring accurate ... Familiarity with AI, language technology, or data annotation projects is a plus.

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All JobsAudio Annotation JobsAudio Annotation Jobs in Newark, NJ

Audio Annotation information

See Newark, NJ salary details

$30.8K

$88.3K

$179.3K

How much do audio annotation jobs pay per year?

As of Sep 3, 2026, the average yearly pay for audio annotation in Newark, NJ is $88,317.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,300.00 and $118,200.00 per year, depending on experience, location, and employer.

What is audio annotation?

Audio annotation is the process of labeling or tagging audio data with relevant information, such as identifying sounds, speech, speakers, or background noises. This process helps train machine learning models to recognize and understand audio content. Audio annotation can involve tasks like transcribing speech, marking segments with specific sounds, or categorizing audio clips by genre or emotion. It is widely used in developing applications for speech recognition, virtual assistants, and audio analysis.

What are the key skills and qualifications needed to thrive as an audio annotator, and why are they important?

To thrive as an Audio Annotator, you need strong attention to detail, excellent listening skills, and familiarity with linguistic concepts, often supported by relevant coursework or experience in linguistics or audio processing. Proficiency in annotation tools such as ELAN, Audacity, or Praat, as well as experience with data labeling platforms, is typically required. Strong organizational skills, patience, and the ability to work independently make someone stand out in this role. These skills ensure accurate and consistent audio data labeling, which is essential for training reliable AI and speech recognition systems.

What are some common challenges faced by audio annotators, and how can they be managed effectively?

Audio annotators often encounter challenges such as distinguishing overlapping voices, dealing with low-quality recordings, and maintaining consistency in labeling. To manage these, it's important to use high-quality headphones, familiarize yourself with annotation guidelines, and communicate regularly with your team to resolve ambiguities. Many organizations also provide regular feedback sessions and quality checks to ensure accuracy and support continuous improvement.

What are popular job titles related to Audio Annotation jobs in Newark, NJ?

For Audio Annotation jobs in Newark, NJ, the most frequently searched job titles are:

What job categories do people searching Audio Annotation jobs in Newark, NJ look for?

The top searched job categories for Audio Annotation jobs in Newark, NJ are:

What cities near Newark, NJ are hiring for Audio Annotation jobs?

Cities near Newark, NJ with the most Audio Annotation job openings:

Audio Annotation jobs near you
Infographic showing various Audio Annotation job openings in Newark, NJ as of August 2026, with employment types broken down into 63% Full Time, 25% Part Time, 5% Temporary, and 7% Contract. Highlights an 81% In-person, 2% Hybrid, and 17% Remote job distribution, with an average salary of $88,317 per year, or $42.5 per hour.

Data Ops Lead

Neonmoneytalks

Manhattan, NY • On-site

$100 - $140/hr

Other

Posted 2 days ago

New

Key responsibilities

  • Own the end-to-end process of transforming raw consumer audio streams into production-ready datasets for AI labs.

  • Manage data deals, ensure dataset quality, and oversee human transcription, annotation, and QA operations, largely overseas.

  • Collaborate with internal teams and external vendors to support data pipeline development and meet buyer specifications.

Job description

About Neon

Many large companies make billions each year by monetizing Americans’ personal data. At Neon, we’re finally cutting consumers in on the deal. Neon allows our users to make hundreds (or even thousands) of dollars per year by securely selling their anonymized data. We’re backed by Lightspeed, Upper90, Upfront Ventures, and other cool investors.

About the role

Your mission is to turn Neon's raw consumer audio streams into the cleanest, most reliable training data on the market, and to build the commercial and operational engine that gets it into the hands of the world's leading AI labs.

As a Data Ops Lead, you'll own the end-to-end journey that takes raw recordings from our growing community of 500,000+ mobile users and delivers production-ready datasets to frontier labs. In practice, that means three things above all:

  • Structuring and managing the data deals that turn our recordings into revenue
  • Holding every dataset to a quality bar that keeps buyers coming back
  • Standing up human transcription, annotation and other operations, largely overseas, that make it all possible

You’ll work directly with our CEO on commercial priorities and help shape each deal, interface with buyer-side engineering and research teams at frontier labs to translate their exact specifications into deliverable dataset plans, and partner with internal engineering and external vendors to make sure the pipeline supports what we’ve sold. This is a foundational role: the datasets and processes you build are the product we sell.

You have…
  • Authorization to work in the US.
  • 5+ years of experience building and scaling data pipelines for AI/ML applications, with significant time spent on audio, speech, or multimodal data.
  • A track record of structuring and delivering against data or dataset agreements with external partners: taking their requirements, turning them into clear specifications, and owning delivery end to end.
  • Experience building and managing overseas or outsourced teams for data tagging, annotation, and QA, with a track record of maintaining quality and throughput across time zones.
  • Deep ownership of data quality: designing QA processes, defining acceptance criteria, and catching problems before a customer ever sees them.
  • Enough technical fluency to be credible on both sides of a deal. You understand digital audio fundamentals (sample rates, VAD, multichannel formats), can reason about how pipelines are built, and know what "good" looks like, even if you’re not writing every line of code yourself.
  • A "Founder's Mentality." You’re comfortable building from zero and making high-stakes calls with incomplete information.
Bonus points
  • A background working with audio data in some capacity.
  • Direct experience with training data for TTS, ASR, speaker ID, or full-duplex conversational models.
  • Familiarity with the modern audio stack (Librosa, FFmpeg, SoX, torchaudio) and cloud data infrastructure (S3, Redshift, BigQuery, or equivalent).
  • An understanding of how high-quality, speaker-separated audio gets captured (for example, via WebRTC-based recording tools).
  • Experience with active learning loops, human-in-the-loop QA systems, or corpus stratification for balanced dataset design.
  • Prior experience leading a data or infrastructure team, including hiring and mentoring engineers.
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