AI Engineer III

Propio Language Services; Fully; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Propio Language Services is hiring an AI Engineer III to design, implement, and deploy practical AI systems spanning speech recognition, LLMs, and prompt engineering. You will work across API integrations, internal tooling, and model pipelines to deliver multilingual retrieval and QA-enhanced solutions.

You will collaborate with cross-functional teams, stay current on trends, and contribute to MVPs that scale toward production handoff.

Qualifikationen

• Master’s degree in engineering or related field.

Aufgaben

• Prototype, build, and deploy end-to-end AI applications involving speech, LLMs, and text generation.

Kenntnisse

Python

Hugging Face Transformers

OpenAI APIs

Whisper

LangChain

Embeddings

Prompt chaining

Pipeline orchestration

Vector databases

FastAPI

Flask

Streamlit

FAISS

Pinecone

Weaviate

Ausbildung

Master’s Degree in Engineering (CS/Statistics/Data Science)

Tools

FastAPI

Flask

Streamlit

FAISS

Pinecone

Weaviate

Jobbeschreibung

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.

Job Type

Full-time

Role

AI Engineer III 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.

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

• 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

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)

Notice of AI Use in Job Application Review

As part of our commitment in creating a fair, efficient, and consistent hiring process we may use artificial intelligence (AI) to help our recruiting teams organize, summarize, and analyze information provided by candidates, including resumes, application responses, and other materials submitted during the application process.AI may be used to identify patterns, highlight relevant skills, and experience, and assist in comparing a candidate’s qualifications with the requirement of a specific role. These tools are to improve efficiency and consistency while supporting more informed hiring decisions, which will ultimately be made by the hiring team.