AI Engineer III
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Job Description
AI Engineer building speech, LLM, and multilingual retrieval tools for Propio’s real-time interpretation services. Deploying practical AI systems, summaries, and interpreter QA workflows.
Responsibilities:
- Prototype, build, and deploy end-to-end AI applications involving speech, LLMs, and text generation
- Integrate APIs such as 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 through a 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 versus build
Requirements:
- Master’s Degree in Engineering, preferably in Computer Science, Statistics, Data Science or equivalent work related experience
- 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, such as using FastAPI, Flask, or Streamlit
- Strong understanding of embeddings, prompt chaining, and pipeline orchestration
- Familiarity with vector databases such as FAISS, Pinecone, or Weaviate
- Comfortable with rapid iteration, MVP mindset, and cross-functional collaboration
- Prior exposure to multilingual or low-resource language challenges is a plus
- 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, including HIPAA, PHI, or Section 1557
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