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Ria Money Transfer

ML & Data Engineer

Ria Money Transfer
Brazil · Full-time · Not Applicable

Description

Ria Money Transfer, a business segment of Euronet Worldwide, Inc. (NASDAQ: EEFT), delivers innovative financial services including fast, secure, and affordable global money transfers to millions of customers along with currency exchange, mobile top-up, bill payment and check cashing services, offering a reliable omnichannel experience.  With over 600,000 locations in nearly 200 countries and territories, our purpose remains to open ways for a better everyday life.

We believe we can create a world in which people are empowered to build the life they dream of, no matter who they are or where they are. One customer, one family, one community at a time.

About This Role

We’re looking for a Machine Learning Engineer with expertise in MLOps, Speech Analytics, and Data Engineering to join our team. In this role, you will design and maintain ML pipelines for real-time and batch workflows, and lead initiatives around automatic transcription and analysis of customer calls, leveraging advanced LLM-based solutions to extract actionable insights and improve customer experience.

Roles & Responsibilities

  • Build and maintain ML pipelines for real-time and batch processing.
  • Develop and deploy solutions for automatic transcription of customer calls using speech-to-text technologies.
  • Create end to end Realtime and batch pipelines from data ingestion to information extraction, to inferences.
  • Monitor and optimize ML systems for performance and data quality.
  • Collaborate with stakeholders to define KPIs and deliver insights from call analytics

Position Requirements

  • 4+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with speech-to-text technologies (AWS Transcribe, Google Speech-to-Text, Whisper).
  • Strong knowledge of NLP techniques for text analytics (sentiment analysis, topic modeling, entity recognition).
  • Familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS).
  • Experience with monitoring and observability tools (Grafana, CloudWatch, Datadog).
  • Excellent problem-solving and communication skills

Preferred Qualifications

  • Experience with LLMs for conversational analysis, summarization, and semantic search.
  • Familiarity with real-time call analytics and voice biometrics.

Perks & Benefits

  • Medical & Dental Coverage (Co-payment model)
  • Life Insurance Policy
  • Daily Food Allowance: R$ 48/day
  • Commuter Subsidy (only for those who go to the office)
  • Corporate Phone
  • Work From Home (WFH)
  • Language Learning Support
  • Fitness & Wellness Subsidy (Wellhub/Gympass)

Ria Money Transfer is an Equal Employment Opportunity employer. All qualified applicants will be considered for employment regardless of age, national origin, race, color, disability, religion, sexual orientation, gender identity or expression, or any other characteristic protected under applicable law. We celebrate diversity and are committed to creating an inclusive environment for all employees.We are committed to providing reasonable accommodations to qualified individuals with disabilities. If you need assistance or an accommodation due to a disability, you may contact us at [email protected].

Check out our website to learn more about the company at: http://www.riamoneytransfer.com/

The position responsibilities outlined above are intended to define the general contents and requirements to perform this job. It is not to be taken as a complete statement of responsibilities or requirements. This job description does not restrict the Company’s right to assign or reassign duties and responsibilities to this job as needed.

Key Skills

Ranked by relevance

machine learning mlops containerization kubernetes tensorflow grafana python docker cloud aws
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Posted
Jun 17, 2026
Type
Full-time
Level
Not Applicable
Location
Barueri

Industries

Financial Services

Categories

Information Technology

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