Sr Machine Learning Engineer - Aws

Lever, Inc.; Partido de Quilmes; On-site; ARS 1,200,000 - 2,400,000; Full time

Job summary

Lever, Inc. is seeking a Machine Learning Engineer with a strong Python background and a focus on NLP to advance document understanding in finance and fintech contexts.

You will build models for reconciliation and accounting tasks, implement OCR and data extraction, and deploy services via Docker and Azure ML. The role requires 2–5 years in ML engineering, with experience in NLP and a finance/fintech environment.

Qualifications

• Proven experience in ML engineering with NLP focus, 2–5 years in finance/fintech.
• Strong Python expertise with Pandas, NumPy, and scikit-learn.
• Experience with NLP libraries (spaCy, NLTK, transformers).
• Familiarity with OCR, PDF parsing, and Excel data extraction.

Responsibilities

• Develop ML models for document understanding and processing.
• Build data pipelines and ETL processes for finance data.
• Deploy models as REST APIs using Docker and Azure ML.
• Apply NLP techniques to reconcile and automate accounting tasks.
• Collaborate with cross-functional teams to meet project goals.

Skills

Python

NLP

LLMs

NLP libraries

Fuzzy matching

Data processing

ML deployment

Supervised learning

Unsupervised learning

Deep learning

Education

Master’s degree in Computer Science or Data Science

Tools

Pandas

NumPy

scikit-learn

spaCy

NLTK

transformers

OCR

PDF parsing

Excel extraction

Docker

Azure ML

Azure Cognitive Services

TensorFlow

PyTorch

OpenAI

Azure 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.

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