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: Bolivia 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.