Senior Machine Learning Engineer

• Job Title: Senior Machine Learning Engineer
• Key Skills: Machine Learning, Python, PySpark, Databricks, MLOps, Kubernetes
• Experience: 5+ YOE.
• Location: Colombia
• Mode: Remote.

We at Coforge are hiring Senior Machine Learning Engineer (#15311-1-5) with the following skill set.

• Key Responsibilities
• · Lead the design and implementation of scalable, production-grade Machine Learning systems in cloud environments.
• · Architect and deliver end-to-end ML solutions, from data ingestion and feature engineering to deployment and monitoring.
• · Design and manage containerized ML workloads using Docker and Kubernetes for model training, batch inference, and real-time serving.
• · Oversee large-scale data pipelines processing multi-terabyte datasets and ensure reliability and performance.
• · Lead experimentation strategies, including A/B testing, model validation, and lifecycle management using platforms such as MLflow and Databricks.
• · Drive continuous model improvement through automated retraining, model monitoring, bias mitigation, and performance optimization.
• · Evaluate and prototype emerging AI/ML technologies, frameworks, and architectures.
• · Collaborate with Product, Engineering, Data, and Leadership teams to define and execute ML initiatives aligned with business goals.
• · Establish engineering standards, code quality practices, and technical documentation.
• · Mentor engineers and provide technical leadership across Machine Learning initiatives.

• 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 building, deploying, and scaling Machine Learning systems.
• · Deep expertise in Python, SQL, and PySpark for distributed data processing.
• · Hands-on experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, and XGBoost.
• · Proven experience designing and managing production ML pipelines using MLflow or similar tools.
• · Experience deploying and operating ML solutions in cloud environments such as AWS, Azure, GCP, or Databricks.
• · Strong understanding of end-to-end ML lifecycles, including data ingestion, training, evaluation, deployment, and monitoring.
• · Hands-on experience with Docker, Kubernetes, and containerized ML workloads.
• · Excellent communication skills and the ability to influence cross-functional teams.

• Preferred Skills
• · Experience working with healthcare datasets, including claims, eligibility, pharmacy, or EHR data.
• · Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, Machine Learning, or a related field.
• · Strong understanding of MLOps practices, including CI/CD for Machine Learning, model versioning, and automated retraining.
• · Experience with deep learning techniques for time series forecasting, sequential data, or hierarchical modeling.
• · Experience designing model evaluation frameworks, experimentation protocols, and performance metrics.
• · Familiarity with Kubernetes-native ML platforms such as Kubeflow, KServe, or Airflow on Kubernetes.
• · Experience working in fast-paced, high-growth environments with multiple concurrent priorities.

Posted On: 09-10-2026

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