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

Fullstack Labs, Inc.; Quilmes; Remote; ARS 139,086,000 - 200,903,000; Full time

Job summary

Fullstack Labs, Inc. is seeking a Machine Learning Engineer focused on NLP and Python to work on document processing in fintech. You will build models for reconciliation and accounting, using OCR, PDFs and Excel data, and deploy REST APIs.

You will collaborate with cross-functional teams, apply fuzzy matching, and leverage Azure ML and Docker for scalable production workflows in a finance-enabled environment.

Qualifications

• Strong Python experience with data manipulation libraries.
• Proficiency in NLP techniques and libraries (spaCy, NLTK, transformers).
• Experience with document processing and OCR workflows.
• Familiarity with fuzzy matching and record linkage concepts.
• ML model deployment via REST APIs; Docker and cloud ML tools.
• Understanding of supervised and unsupervised learning methods.
• Exposure to TensorFlow or PyTorch is a plus.

Responsibilities

• Develop ML models for document understanding and processing.
• Use Pandas, NumPy and scikit-learn for data analysis.
• Apply NLP techniques with spaCy, NLTK or transformers.
• Implement fuzzy matching for data accuracy.
• Process documents via OCR, PDF parsing, and Excel extraction.
• Deploy models as REST APIs using Docker and Azure ML.
• Design data pipelines and ETL workflows.
• Collaborate with cross-functional teams to meet project goals.

Skills

Python

NLP

Pandas

NumPy

scikit-learn

OCR

REST APIs

Docker

Azure ML

Deep learning

Tools

Docker

Azure ML

SpaCy

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