Senior ML Ops Engineer: NLP for Fintech Systems

Fullstack; Buenos Aires; Remote; ARS 2,000,000 - 3,000,000; Full time

Job summary

Fullstack is seeking a Machine Learning Engineer with a strong Python background and a focus on NLP to join our team in the finance/fintech domain. The role involves building document understanding models, applying NLP techniques, and deploying solutions as REST APIs using Docker and Azure ML.

You will work on data pipelines, ETL processes, and collaborate across teams to meet project goals, leveraging OCR, PDF parsing, and Excel extraction for document processing.

Qualifications

• 2–5 years of experience in ML engineering, focusing on NLP or financial data processing.
• Experience in the finance/fintech domain (reconciliation, accounting).
• Master’s degree in Computer Science, Data Science, or a related field.

Responsibilities

• Develop and implement machine learning models for document understanding and processing.
• Utilize Python libraries for data manipulation and analysis.
• Apply NLP techniques using spaCy, NLTK, or transformers.
• Implement fuzzy matching algorithms for data accuracy.
• Process documents using OCR, PDF parsing, and Excel data extraction methods.
• Deploy machine learning models as REST APIs using Docker and Azure ML.
• Understand and apply supervised and unsupervised learning techniques.
• Design and manage data pipelines and ETL processes.
• Collaborate with cross-functional teams to meet project goals.

Skills

Python

Pandas

NumPy

scikit-learn

NLP

spaCy

NLTK

Transformers

OCR

REST APIs

Docker

Azure ML

LLMs

TensorFlow

PyTorch

Data Pipelines

Education

Master’s degree in Computer Science

Tools

Docker

Azure ML

Azure Cognitive Services

OCR libraries

Job description

Fullstack is seeking a Machine Learning Engineer with a strong Python background and a focus on NLP to join our team in the finance/fintech domain. The role involves building document understanding models, applying NLP techniques, and deploying solutions as REST APIs using Docker and Azure ML.

You will work on data pipelines, ETL processes, and collaborate across teams to meet project goals, leveraging OCR, PDF parsing, and Excel extraction for document processing.