Senior Ml Engineer - Remote Aws Mlops Leader

Allshore Talent; Buenos Aires; Remote; ARS 800,000 - 1,000,000; Full time

Job summary

Allshore Talent seeks a Machine Learning Engineer with a strong Python/NLP focus to join our team. You will build models for document understanding, use LaTeX alignment for data pipelines, and deploy via REST APIs.

The role emphasizes finance/fintech data processing and collaboration with cross-functional teams. The ideal candidate has 2–5 years in ML engineering, NLP expertise, and experience with OCR/PDF/Excel extraction, and DL frameworks such as TensorFlow or PyTorch.

Qualifications

• Master’s degree in Computer Science, Data Science, or related field.
• 2–5 years of ML engineering experience, NLP focus preferred.
• Strong Python expertise with Pandas, NumPy, scikit-learn.
• Experience with NLP libraries: spaCy, NLTK, transformers.
• Familiarity with OCR, PDF parsing, and Excel data extraction.
• ML deployment via REST APIs, Docker, and Azure ML.
• Experience with LLMs (OpenAI, Azure OpenAI) and DL frameworks.

Responsibilities

• Develop and implement ML models for document understanding.
• Use Python libraries for data manipulation and analysis.
• Apply NLP techniques for processing and extraction.
• Design data pipelines and ETL processes.
• Collaborate with cross-functional teams to meet goals.

Skills

Python

Pandas

NumPy

scikit-learn

spaCy

NLTK

transformers

Fuzzy matching

OCR

REST APIs

Docker

Azure ML

TensorFlow

PyTorch

LLMs

OpenAI

Azure Cognitive Services

Education

Master’s degree in Computer Science or Data Science

Tools

Docker

Azure ML

TensorFlow

PyTorch

OpenAI

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.