NLP ML Engineer - Python, Cloud, Fintech Doc Processing

Fullstack; Quilmes; Remote; ARS 1,200,000 - 1,800,000; Full time

Job summary

Fullstack is seeking a Machine Learning Engineer with strong Python and NLP focus to join our fintech-focused team in Argentina. You will develop models for document understanding, leverage OCR and data extraction, and deploy REST APIs via Docker and Azure ML.

You will work with cross-functional teams on reconciliation and accounting data, applying transformers, spaCy and NLTK, and leveraging LLMs for document comprehension in a finance context.

Qualifications

• Master's degree or equivalent in CS/DS
• 2–5 years of ML engineering experience, focused on NLP or financial data
• Strong Python data-science stack
• Experience in fintech or reconciliation domain is a plus

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

OCR/Document Processing

REST APIs / Docker / Azure ML

Fuzzy matching

LLMs / OpenAI

Education

Master’s degree in Computer Science / Data Science

Tools

Docker

Azure ML

Azure Cognitive Services

REST APIs

Job description

Fullstack is seeking a Machine Learning Engineer with strong Python and NLP focus to join our fintech-focused team in Argentina. You will develop models for document understanding, leverage OCR and data extraction, and deploy REST APIs via Docker and Azure ML.

You will work with cross-functional teams on reconciliation and accounting data, applying transformers, spaCy and NLTK, and leveraging LLMs for document comprehension in a finance context.