Senior Ml Ops Engineer - Remote | Python & Cloud

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

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 Large Language Models (LLMs) for document understanding (OpenAI, Azure OpenAI).
• Knowledge of Azure ML services and Azure Cognitive Services.
• 2-5 years of experience in ML engineering, focusing on NLP or financial data processing.
• Experience in the finance/fintech domain (reconciliation, accounting).

Education

• Master’s degree in Computer Science, Data Science, or a related field.