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Sobre esta vaga de QA Specialist na HumanSignal

HumanSignal · Presencial · Hoboken, NJ

About HumanSignal

Real-world data is the competitive edge in AI.

HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.


We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.


We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.


If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.

QA Specialist

HumanSignal is looking for QA Specialists to support an audio and video data processing project. You'll work with recorded media files, align audio and video, trim recordings, and perform quality checks using our Label Studio platform and established processing guidelines.

This is a hands-on, detail-oriented role that could be a great fit for individuals with experience in data annotation, media editing, quality assurance, or anyone who is tech-savvy, organized, and comfortable working with digital tools.

What you’ll do

  • Retrieve and organize audio and video recordings from designated storage locations and import them into Label Studio.
  • Synchronize multiple audio and video recordings, aligning footage and audio waveforms to the correct timestamps according to project guidelines.
  • Trim recordings to the required start and end points, ensuring all relevant content is retained.
  • Follow established playbooks for media alignment, trimming, file naming, export settings, and file size requirements.
  • Perform quality checks to identify missing files, synchronization errors, incomplete recordings, or other inconsistencies.
  • Save, export, and organize completed files according to the required formats and submission procedures.
  • Troubleshoot basic processing or platform issues, proactively flagging problems and escalating concerns when needed.
  • Maintain accuracy and consistency while meeting expected daily processing and quality targets.
  • Communicate progress, blockers, and recurring issues to the project team to help improve workflows.

Who you are

  • You're detail-oriented, organized, and comfortable working on tasks that require accuracy and consistency.
  • You're tech-savvy and confident learning new software, platforms, and digital workflows.
  • You can follow detailed instructions and established guidelines with minimal supervision.
  • You're proactive, resourceful, and comfortable troubleshooting issues as they arise.
  • You communicate clearly and raise concerns early when something doesn't look right.
  • You can manage repetitive, detail-heavy tasks while maintaining quality and meeting deadlines.
  • Experience with data annotation, quality assurance, audio/video editing, or media processing is a plus, but not required.

Details

  • Contract Duration: To be confirmed during the recruitment process
  • Up to 40 hours per week
  • $30 to $50 per hour, depending on relevant experience
  • Occasional evening and weekend availability required
  • Remote-US role with team based in Hoboken, NJ and surrounding areas
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Como este salário de Quality Assurance se compara

Esta vaga paga $83,200/yr — em linha com da faixa típica para vagas de Quality Assurance.

$62,869 a mediana $108,570 $158,683

Faixa típica $80,372–$136,834/yr, com base em 292 vagas de Quality Assurance comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Quality Assurance →

Sobre a HumanSignal

We build software that helps people do what only they can do – give meaning.

Data fills our modern world. It flows prolifically inside organizations, customer interactions, product usage, environmental research, healthcare imaging, and beyond. What if we could use any of this historical data to predict the future? In most cases, we can now make predictions through Machine Learning & AI, but to do so in a meaningful and impactful way, historical data needs to be accurate, comprehensive, and without bias.

 

To make the best predictions, we believe teams with domain expertise should be responsible for annotating and curating data. It's called data labeling, and it’s a process of real people giving meaning to the information they see on the screen. HumanSignal was founded to take data labeling operations to the next level and help data scientists make better predictions.

Ver todas as vagas na HumanSignal →

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