Remote Nlp & Ml Engineer For Finance Data Insights

Ryzlabs; Quilmes; Remote; ARS 2,000,000 - 4,000,000; Full time

Job summary

Ryzlabs in Argentina is seeking an Applied ML Engineer (Senior) to lead the development and operationalization of machine learning models powering real-world AI products, with a focus on speech-to-text (ASR) for medical conversations in Brazilian Portuguese and Latin American Spanish.

You will design and deploy end-to-end ML solutions, build training pipelines, and collaborate with product and domain teams to translate business needs into scalable ML systems, taking models from experimentation

Qualifications

• Experience building ML models for speech and language applications.
• Hands-on role from experimentation to production.

Responsibilities

• Design, train, fine-tune, and deploy ML models for speech and language applications.
• Build and maintain training pipelines and evaluation frameworks.
• Work on ASR systems for domain-specific medical conversations.
• Develop and improve data pipelines and ML infrastructure.
• Collaborate on LLM fine-tuning and classifier development.
• Optimize model performance, reliability, and scalability.
• Partner with product and domain teams to translate business needs into ML solutions.
• Contribute to production deployment and monitoring of ML systems.

Skills

ML engineering

ASR systems

LLM fine-tuning

ML infrastructure

Job description

Applied ML Engineer (Speech/ASR/LLMs) - Senior (Brazil / Argentina)

About the role

We're looking for an Applied ML Engineer to lead the development and operationalization of machine learning models powering real-world AI products.

The primary focus of the role will be building and improving speech-to-text (ASR) systems for medical conversations in Brazilian Portuguese and Latin American Spanish, while also contributing to LLM fine-tuning, clinical classifiers, and production ML infrastructure.

This is a highly hands-on role focused on taking models from experimentation to production.

What you’ll do

• Design, train, fine-tune, and deploy ML models for speech and language applications
• Build and maintain training pipelines and evaluation frameworks
• Work on ASR systems for domain-specific medical conversations
• Develop and improve data pipelines and ML infrastructure
• Collaborate on LLM fine-tuning and classifier development
• Optimize model performance, reliability, and scalability
• Partner with product and domain teams to translate business needs into ML solutions
• Contribute to production deployment and monitoring of ML systems