Note: The job is a remote job and is open to candidates in USA. Propio Language Services provides real-time interpretation and multilingual language services and is building AI-powered tools to improve interpreter workflows and communication quality. The AI Engineer III will build and deploy AI systems involving speech recognition, large language models, prompt engineering, text generation, and multilingual retrieval, while collaborating across engineering, research, product, and MLOps.
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
Skills
- 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 (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
- 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)
Company Overview