Remote ML Engineer — Scalable Models & Pipelines

Engg; Colombia; Presencial; COP 90.000.000 - 150.000.000; Jornada completa

Descripción de la vacante

Coforge is hiring a Mid Machine Learning Engineer to design, develop, and deploy scalable ML models in cloud environments. You will build robust data pipelines, perform feature engineering on large datasets, and manage the full ML lifecycle from experimentation to deployment.

Candidates should have 3+ years of experience with Python/SQL/PySpark and strong ML framework skills, plus cloud experience across AWS/GCP/Azure or Databricks. Remote work option available.

Formación

• 3+ years of experience as an ML Engineer, Data Scientist, or Data Engineer.
• Strong proficiency in Python, SQL, and PySpark for large-scale data processing.
• Hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Experience with ML pipeline and model management tools such as MLflow or equivalent.
• Experience with cloud-based environments including AWS, Google Cloud, Azure, or Databricks.

Responsabilidades

• Design, develop, deploy, and maintain scalable production-grade ML models and pipelines in cloud environments.
• Architect and optimize data ingestion pipelines, feature engineering, and label sets for multi-terabyte datasets.
• Manage end-to-end ML lifecycle, including experimentation, training, validation, versioning, deployment, monitoring, and improvement.
• Collaborate with product, engineering, and business stakeholders to translate requirements into ML solutions and prototype new tech.

Conocimientos

Python

SQL

PySpark

Machine Learning

MLflow

Databricks

scikit-learn

XGBoost

PyTorch

TensorFlow

Educación

Bachelor's or Master's in Computer Science, Machine Learning, Data Science, or related field

Herramientas

Databricks

MLflow

AWS

Google Cloud

Azure

Descripción del empleo

Coforge is hiring a Mid Machine Learning Engineer to design, develop, and deploy scalable ML models in cloud environments. You will build robust data pipelines, perform feature engineering on large datasets, and manage the full ML lifecycle from experimentation to deployment.

Candidates should have 3+ years of experience with Python/SQL/PySpark and strong ML framework skills, plus cloud experience across AWS/GCP/Azure or Databricks. Remote work option available.