Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Key Skills: Python, SQL, PySpark, Machine Learning, Scikit-learn, PyTorch, XGBoost, TensorFlow, ML Pipelines, MLflow, Databricks, AWS, Azure, GCP, Kubernetes, MLOps

Experience: 5+ YOE

Location: LATAM (Guatemala, Honduras, El Salvador, Nicaragua, Panama, Colombia, Perú, Mexico, Costa Rica, Brazil, Ecuador, Paraguay, Uruguay)

Modality: Remote

We at Coforge are hiring Senior Machine Learning Engineer (Job# 15311-1-1) with the following skill set.

Key Responsibilities

Design, develop, and deploy scalable machine learning solutions in production environments.

Build and optimize end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.

Develop distributed data processing workflows using PySpark and SQL to support large-scale ML applications.

Collaborate with Data Scientists, Data Engineers, Product Teams, and business stakeholders to translate business requirements into ML solutions.

Deploy and manage machine learning models across cloud platforms such as AWS, Azure, GCP, and Databricks.

Implement MLOps best practices, including model versioning, experiment tracking, CI/CD, monitoring, and lifecycle management.

Design and maintain containerized ML workloads leveraging Kubernetes for model serving, batch processing, and orchestration.

Drive improvements in model performance, scalability, reliability, and operational efficiency.

Required Skills & Qualifications

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).

5+ years of experience as a Machine Learning Engineer, focused on production-grade ML systems.

Strong programming experience with Python, SQL, and PySpark for large-scale data processing.

Hands-on experience with machine learning frameworks and libraries such as Scikit-learn, PyTorch, TensorFlow, and XGBoost.

Proven expertise building and maintaining robust ML pipelines using MLflow or similar MLOps platforms.

Experience deploying and managing machine learning solutions in cloud environments, including AWS, Azure, GCP, and Databricks.

Strong understanding of the complete ML lifecycle, from data preparation to production monitoring and maintenance.

Experience working with Kubernetes and containerized workloads for machine learning applications.

Excellent communication skills with the ability to collaborate effectively across cross-functional teams.

Preferred Skills

Experience with MLOps, CI/CD pipelines, and model governance frameworks.

Knowledge of model monitoring, observability, and performance optimization techniques.

Experience working in Agile development environments.

Familiarity with Docker, workflow orchestration tools, and large-scale distributed computing platforms.

Exposure to generative AI, LLMs, or advanced machine learning systems is a plus.

Posted On: Sept 23rd 2026

At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.