
Senior Machine Learning Engineer
Encora · Colombia
- IT Services & Consulting
- 10,001+ employees
- Noida, Uttar Pradesh
Mixed hiring record · median 25 days open
All reasons
- 29% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
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.
Skills
- Machine Learning
- Python
- PySpark
- Databricks
- MLOps
- Kubernetes
- Docker
- MLflow
- SQL
- scikit-learn
- PyTorch
- TensorFlow
- XGBoost
- AWS
- Azure
- GCP
- Deep Learning
- Kubeflow
- Airflow
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