What are the responsibilities and job description for the Applied AI Engineer position at Propio Language Services?
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
Qualifications:
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
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
- 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)