Machine Learning Operations Engineer (Ai/Ml) - Remote - Latin America

Fullstack Labs, Inc.; Buenos Aires; Remote; ARS 64,907,000 - 101,997,000; Full time

Job summary

Fullstack Labs, Inc. is seeking a Machine Learning Engineer focused on NLP to build document understanding models for finance-related reconciliation and accounting tasks. You will work with Python data tools, implement NLP workflows with spaCy/NLTK/transformers, and deploy models as REST APIs.

Responsibilities include developing ML solutions, handling OCR/PDF/Excel data extraction, and building scalable data pipelines. Collaboration with cross-functional teams is essential in a fintech context.

Qualifications

• Proven experience building NLP-driven ML models for document understanding.
• Experience deploying ML models as REST APIs.
• Strong Python data manipulation and ML model development skills.

Responsibilities

• Develop and implement machine learning models for document understanding and processing.
• Utilize Python libraries such as Pandas, NumPy, and scikit-learn for data manipulation and analysis.
• Apply NLP techniques using libraries like 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

fuzzy matching

OCR

PDF parsing

Excel extraction

supervised learning

unsupervised learning

TensorFlow

PyTorch

deep learning

Tools

Docker

Azure ML

REST APIs

Job description

We are seeking a Machine Learning Engineer with strong expertise in Python and a focus on Natural Language Processing (NLP) to join our team. The ideal candidate will have experience in the finance or fintech domain, specifically in reconciliation and accounting.

Responsibilities

• Develop and implement machine learning models for document understanding and processing.
• Utilize Python libraries such as Pandas, NumPy, and scikit-learn for data manipulation and analysis.
• Apply NLP techniques using libraries like spaCy, NLTK, or transformers.
• Implement fuzzy matching algorithms (., Levenshtein distance, record linkage) 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.

Required Skills

• Strong expertise in Python (Pandas, NumPy, scikit-learn).
• Experience with NLP libraries (spaCy, NLTK, transformers).
• Knowledge of fuzzy matching algorithms.
• Document processing skills (OCR, PDF parsing, Excel extraction).
• Experience in ML model deployment (REST APIs, Docker, Azure ML).
• Understanding of supervised/unsupervised learning techniques.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch).
• Experience with