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Audio Speech Machine Learning Jobs in Indiana (NOW HIRING)

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$20/hr

Proficiency in data annotation, labeling, or preparation for machine learning * Exceptional ... Familiarity with multiple data types (text, image, audio, video)

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Audio Speech Machine Learning information

What are some common challenges faced when developing machine learning models for audio speech applications?

A key challenge in audio speech machine learning roles is dealing with diverse and noisy audio data, which can significantly affect model accuracy. Additionally, models must be robust to different accents, languages, and speaking styles, requiring large and varied datasets for training and validation. Collaboration with data engineers, linguists, and software developers is often necessary to ensure high-quality data pipelines and model integration into production systems. Staying updated with the latest research and optimizing models for real-time performance are also ongoing aspects of the role.

What is an Audio Speech Machine Learning Engineer?

An Audio Speech Machine Learning Engineer is a specialized professional who designs, develops, and implements machine learning models that process and analyze audio and speech data. Their work involves tasks like speech recognition, speaker identification, and audio event detection by leveraging algorithms and large datasets. These engineers collaborate with data scientists, software developers, and linguists to create applications such as voice assistants, transcription tools, and automated customer service systems. Expertise in signal processing, deep learning frameworks, and programming languages like Python is crucial for this role.

What is the difference between Audio Speech Machine Learning vs Speech Data Analyst?

AspectAudio Speech Machine LearningSpeech Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Data Analysis, Statistics, or related fields; experience with data tools
Work EnvironmentResearch labs, tech companies, AI startupsData analysis teams, research institutions, tech firms
Industry UsageDeveloping speech recognition, voice assistants, NLP applicationsAnalyzing speech datasets, improving speech models, reporting insights

Audio Speech Machine Learning focuses on developing algorithms for speech recognition and processing, often involving model training and AI development. Speech Data Analysts interpret speech data, generate insights, and support model improvements. Both roles require strong analytical skills, but their core tasks differ: one builds models, the other analyzes data.

What are the key skills and qualifications needed to thrive as an Audio Speech Machine Learning Engineer, and why are they important?

To thrive as an Audio Speech Machine Learning Engineer, you need a solid background in machine learning, signal processing, and programming (typically Python), along with a relevant degree in computer science or a related field. Familiarity with tools like TensorFlow or PyTorch, audio processing libraries (such as Librosa), and experience with speech datasets and ASR systems are commonly required. Critical soft skills include problem-solving, innovation, and effective communication for collaborating with cross-functional teams. These skills are essential to develop accurate, scalable speech recognition systems that advance voice-driven technology.
What are popular job titles related to Audio Speech Machine Learning jobs in Indiana? For Audio Speech Machine Learning jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Audio Speech Machine Learning jobs in Indiana look for? The top searched job categories for Audio Speech Machine Learning jobs in Indiana are:
What cities in Indiana are hiring for Audio Speech Machine Learning jobs? Cities in Indiana with the most Audio Speech Machine Learning job openings:
Audio Speech Machine Learning jobs near you

Audio Collection & Transcription - Native U.S. English Speakers

Chemin

Brazil, IN • Remote

Other

Posted 4 days ago

Job description

About Kaya

Kaya by Chemin Sdn Bhd is a community for high-performing data annotators who play an integral role in shaping the future of machine learning and artificial intelligence.

Kaya offers a collaborative environment where ambitious annotators can thrive. It is a tight-knit community that supports members' professional growth and helps them build a long-term career in data labelling and AI.

Join Kaya and start contributing to impactful AI projects.

About the Role

We are looking for native U.S. English speakers to join a short-term remote project helping train AI language systems.

Your task in this project is to record natural customer service conversations based on client-provided scripts and accurately transcribe your own recordings. These conversations reflect how people naturally speak in real-life customer service interactions, helping AI better understand authentic U.S. English speech.

If you're comfortable working with audio, detail-oriented, and can commit a few hours a day, this project is for you.

Requirements

What You'll Be Doing
  • Record natural customer service conversations by following client-provided scripts
  • Transcribe your own recordings accurately
  • Segment audio into natural speech units
  • Identify and label speakers when multiple voices are present
  • Apply transcription guidelines, punctuation, and annotation tags correctly
  • Follow project guidelines to maintain high-quality outputs
  • Communicate actively with the Project Manager for clarifications
Project Details
  • Duration: Approximately 2 months
  • Time commitment: Around 4-6 hours per day
  • Onboarding Training: Mandatory (TBD, during office hours 9:00 AM-6:00 PM GMT-3)
  • Working hours: Flexible (tasks can be completed anytime before the assigned deadline)
Pay Rate
  • Audio Collection: USD 1 per accepted audio minute
  • Transcription: USD 2 per accepted task (AHT: ~30-60 minutes per task)
  • Project Period: July - August 2026
What Do I Need?
  • Native speaker of U.S. English
  • Strong listening, reading, and writing skills in English
  • Excellent attention to detail and ability to follow written guidelines
  • Detail-oriented and patient, able to maintain at least 95% accuracy
  • Willing to ask questions when unsure
  • Quiet environment suitable for recording audio
  • Laptop or desktop with a stable internet connection
  • Ability to manage your own time and meet deadlines
  • Willing to complete a mandatory pre-assessment as part of the screening process, assessment here: https://forms.gle/Vkhfz2fGVXiWvHMv6

A mandatory pre-assessment will be shared to evaluate whether your skill and language proficiency meets the project's quality standards.

Bonus point: Previous experience in transcription, audio annotation, data labelling, or AI-related projects.

Benefits

    • Work remotely from anywhere
    • Be part of an AI project representing authentic U.S. English conversations
    • Priority consideration for future opportunities
    • Gain hands-on experience in AI language data, transcription, and audio annotation
    • Contribute to building smarter and more inclusive AI language technologies

Apply