Senior Ml Ops Engineer: Production Ml & Cloud Automation

Fullstack; Quilmes; On-site; ARS 90,873,000 - 136,310,000; Full time

Job summary

Fullstack seeks a Machine Learning Engineer with strong Python and NLP focus to join our team in Buenos Aires. You will develop models for document understanding in finance, handling reconciliation and accounting data.

Responsibilities include building NLP models, implementing fuzzy matching, OCR processing, and deploying REST APIs with Docker and Azure ML. 2–5 years in NLP/fintech data is ideal.

Qualifications

• Master’s degree in Computer Science, Data Science, or related field.
• 2–5 years of ML engineering experience, focusing on NLP or financial data processing.
• Strong Python experience with Pandas, NumPy, and scikit-learn.
• Experience with NLP libraries (spaCy, NLTK, transformers) and LLMs.

Responsibilities

• Develop ML models for document understanding and processing in finance/fintech.
• Apply NLP techniques and fuzzy matching for data accuracy.
• Process documents with OCR, PDF parsing, and Excel extraction.
• Deploy models as REST APIs using Docker and Azure ML.
• Design data pipelines and ETL processes.
• Collaborate with cross-functional teams to meet goals.

Skills

Python

Pandas

NumPy

scikit-learn

NLP

spaCy

NLTK

transformers

fuzzy matching

OCR

PDF parsing

Excel extraction

Docker

Azure ML

Azure Cognitive Services

LLMs

Education

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

Tools

Docker

Azure ML

Azure Cognitive Services

TensorFlow

PyTorch

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.