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Audio Annotation Jobs in Kansas (NOW HIRING)

Propio

Applied AI Engineer

Overland Park, KS · On-site

Experience with data labeling, annotation, or active learning workflows * Familiarity with real-time audio processing or latency-sensitive applications * Experience in healthcare, legal, or regulated ...

Propio

Applied AI Engineer

Overland Park, KS · On-site

Experience with data labeling, annotation, or active learning workflows * Familiarity with real-time audio processing or latency-sensitive applications * Experience in healthcare, legal, or regulated ...

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Audio Annotation information

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 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.
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What cities in Kansas are hiring for Audio Annotation jobs? Cities in Kansas with the most Audio Annotation job openings:
Audio Annotation jobs near you
Infographic showing various Audio Annotation job openings in Kansas as of May 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution.
Applied AI Engineer

Applied AI Engineer

Propio

Overland Park, KS • On-site

Other

Posted 13 days ago

Propio rating

7.7

Company rating: 7.7 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

137th of 425 rated business services

Job description

Description


Propio is on a mission to make communication accessible to everyone. As a leader in real-time interpretation and multilingual language services, we connect people with the information they need across language, culture, and modality. We're committed to building AI-powered tools to enhance interpreter workflows, automate multilingual insights, and scale communication quality across industries. 


We are hiring an Applied AI Engineer to build and deploy practical, high-impact AI systems. You will work across speech recognition, large language models, and prompt engineering to ship products like AI-generated summaries, interpreter QA tools, and multilingual retrieval systems. You'll operate at the intersection of engineering, research, and product with high ownership and startup-level pace.


This is a builder role, not a research-only position and you will be working closely with our VP of AI to get things live, fast.


Key Responsibilities: 

  • Prototype, build, and deploy end-to-end AI applications involving speech, LLMs, and text generation
  • Integrate APIs like OpenAI, Whisper, Deepgram, and open-source equivalents for ASR and NLP
  • Collaborate with Engineers to iterate and refine MVPs before transitioning to model-level optimization
  • Develop internal tools and dashboards to test summarization, QA scoring, and multilingual understanding
  • Rapidly test ideas and model variations to explore feasibility and impact (build-measure-learn loop)
  • Ensure model pipelines are robust, scalable, and ready for handoff to MLOps and production
  • Work with the AI PM to align technical outputs with business use cases and feedback loops
  • Stay current on applied AI trends in speech and LLMs, and advise on what to use vs. build

Requirements


Qualifications:

  • Master's Degree in Engineering, preferably in Computer Science, Statistics, Data Science or equivalent work related experience 
  • 3-5+ years of experience working with NLP or speech models in real-world applications
  • Experience with Python, Hugging Face Transformers, OpenAI APIs, Whisper, LangChain, or similar frameworks
  • Experience deploying AI models in production or pilot environments (e.g., using FastAPI, Flask, or Streamlit)
  • Strong understanding of embeddings, prompt chaining, and pipeline orchestration
  • Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate)
  • Comfortable with rapid iteration, MVP mindset, and cross-functional collaboration
  • Prior exposure to multilingual or low-resource language challenges is a plus


Preferred Qualifications:

  • Experience building speech-to-text pipelines or hybrid ASR + LLM systems
  • Experience with data labeling, annotation, or active learning workflows
  • Familiarity with real-time audio processing or latency-sensitive applications
  • Experience in healthcare, legal, or regulated environments (HIPAA, PHI, Section 1557)

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