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.