Machine Learning Ops Engineer

JPMorgan Chase & Co.; Buenos Aires; Presencial; ARS 129.584.000 - 172.779.000; Jornada completa

Descripción de la vacante

A leading financial services firm is seeking a Machine Learning Data Scientist Specialist in Buenos Aires. The role involves developing, deploying, and optimizing machine learning models, fine-tuning algorithms, and integrating capabilities into products. Ideal candidates will have expertise in ML, data science, cloud services, and strong coding skills. You will collaborate with teams and enhance predictive data capabilities, making a significant impact in the organization.

Responsabilidades

• Research, develop, and optimize machine learning models for various applications/web use interface.
• Fine-tune pre-trained models using domain-specific datasets.
• Implement, evaluate, and improve ML pipelines to enhance model performance.
• Design efficient training workflows and optimize inference performance.
• Work with cross-functional teams to integrate ML capabilities into products.
• Conduct rigorous testing and benchmarking of ML models.

Conocimientos

ML algorithms

Statistical modelling

Predictive analytics

Data preprocessing

Feature engineering

Data visualization

Exploratory data analysis

Cloud computing services

MLOps tools

Big data technologies

Python

R

Scala

Scikit-Learn

Pandas

NumPy

Problem-solving

Descripción del empleo

About the Role:

Machine Learning Data Scientist Specialist to drive the development, deployment, and optimization of machine learning models. The ideal candidate will have expertise in data science, machine learning (ML), and AI model fine-tuning. You will be responsible for training, fine‑tuning, evaluating, and integrating language models into various applications/web use interface using Infinite AI Training/serving architecture to accelerate our ability to deliver predictive data capabilities in the Technology Operate and Production Management Team.

Key Responsibilities:

• Research, develop, and optimize machine learning models for various applications/ web use interface
• Fine‑tune pre‑trained models using domain‑specific datasets.
• Implement, evaluate, and improve ML pipelines to enhance model performance.
• Design efficient training workflows and optimize inference performance.
• Work with cross‑functional teams to integrate ML capabilities into products.
• Conduct rigorous testing and benchmarking of ML models.

Required Skills and Experience:

• Experience with ML algorithms, statistical modelling, and predictive analytics.
• Proficiency in data preprocessing, feature engineering, and model evaluation.
• Experience in data visualization and exploratory data analysis (EDA).
• Hands‑on experience with cloud computing services (AWS, GCP, Azure) and MLOps tools.
• Knowledge of big data technologies such as Spark, Hadoop, or distributed computing frameworks.
• Strong coding skills in Python, R, or Scala and familiarity with relevant libraries (Scikit‑Learn, Pandas, NumPy).
• Excellent problem‑solving skills and ability to work in a collaborative team environment.