Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

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

Experience: 5+ YOE.

Location: Costa Rica

Mode: Remote

We at Coforge are hiring Senior Machine Learning Engineer (#20529) with the following skill set.

Key Responsibilities

• Design, deploy, and scale machine learning systems and end-to-end ML pipelines in production environments.
• Build and optimize distributed data processing workflows using Python, SQL, and PySpark.
• Manage the complete ML lifecycle, including data ingestion, training, evaluation, deployment, monitoring, and model optimization.
• Collaborate with cross-functional teams to deliver scalable ML solutions and improve model performance in cloud-based environments.

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 industry experience as an ML Engineer with a focus on deploying and scaling ML systems.
• Strong expertise in Python, SQL, and PySpark for distributed data processing.
• Experience with machine learning frameworks such as scikit-learn, TensorFlow, XGBoost, and PyTorch.
• Proven experience designing and managing ML pipelines using tools like MLflow or equivalent.
• Hands-on experience deploying models in cloud environments such as AWS, GCP, Azure, or Databricks.
• Experience managing end-to-end ML lifecycles at scale, including deployment and monitoring.
• Experience deploying and managing containerized ML workloads using Kubernetes.
• Strong communication skills and the ability to collaborate across technical and business teams.
• Experience working in fast-paced, high-impact environments with multiple priorities.

Preferred Skills:

• Experience working with healthcare data, including medical claims, pharmacy claims, eligibility data, and EHR systems.
• Knowledge of MLOps practices including CI/CD for ML, automated retraining, and model versioning.
• Experience with deep learning architectures for forecasting, sequential data, or hierarchical modeling.
• Familiarity with Kubernetes-native ML tools such as Kubeflow, KServe, or Airflow on Kubernetes.
• Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or a related field.

Posted On: 29-05-2026

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.