Senior Machine Learning Engineer
AI Summary
Senior ML Engineer focuses on designing, deploying, and scaling end-to-end ML systems and pipelines in production, leveraging Python, SQL, PySpark, and cloud platforms.
About this role
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.
