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.
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