Propio is looking to build cutting-edge products using large language models (LLMs) to make communication accessible to everyone by enhancing interpreter workflows, automating multilingual insights, and scaling communication quality across industries. The LLM AI Engineer will help build systems that summarize, translate, evaluate, and structure multilingual interpretation content in real time.
Requirements
- 3+ years of experience working with NLP or large-scale ML models in production
- Strong understanding of transformer architectures and recent LLM developments (e.g., LoRA, RAG, PEFT)
- Hands-on experience with one or more frameworks: Hugging Face, LangChain, OpenAI APIs, DeepSpeed, or vLLM
- Proven experience building multilingual or domain-adapted LLM pipelines
- Familiarity with retrieval-augmented generation (RAG), vector stores (FAISS, Weaviate), and prompt evaluation
- Strong Python skills and comfort working in Git-based, containerized environments
- Experience training or fine-tuning open-source LLMs from scratch
Responsibilities
- Fine-tune, evaluate, and deploy LLMs (e.g., Mistral, GPT, Claude, LLaMA) for summarization, QA, and multilingual tasks
- Build and optimize embedding pipelines, RAG systems, and vector search capabilities for document/question retrieval
- Work with Prompt Engineers to prototype use cases before transitioning to model-level customization
- Develop evaluation frameworks for language generation quality, semantic preservation, and multilingual fluency
- Collaborate with AI Product Manager to translate business requirements into scalable model solutions
- Work with MLOps to ship models into production with robust monitoring and fallback mechanisms
- Stay up to date with open-source developments and help evaluate new foundation models and libraries
Other
- Master’s Degree in Engineering, preferably in Computer Science, Statistics, Data Science or equivalent work experience
- Experience with healthcare or regulated domains a plus (e.g., HIPAA, PHI-safe modeling)
- Prior work in translation, interpretation, summarization, or cross-lingual QA
- Contributions to open-source NLP projects
- Experience working with speech-to-text pipelines or multimodal systems
