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.

📌 Senior Machine Learning Engineer (Bogotá)
🏢 Encora
📍 Bogotá