Job Title: Mid Machine Learning Engineer
Key Skills: Python, SQL, PySpark, Machine Learning, MLflow, Databricks, scikit-learn, XGBoost, PyTorch, TensorFlow, Cloud Platforms
Experience: 3+ YOE.
Location: Open to candidates from approved hiring locations.
Mode: Remote.
We at Coforge are hiring Mid Machine Learning Engineer (#15311-1-3) with the following skill set.
Key Responsibilities
Design, develop, deploy, and maintain scalable production-grade machine learning models and pipelines in cloud environments.
Architect and optimize data ingestion pipelines, feature engineering, and label sets for multi-terabyte clinical and consumer datasets.
Manage the end-to-end ML lifecycle, including experimentation, training, validation, versioning, deployment, monitoring, and continuous model improvement.
Collaborate with product, engineering, and business stakeholders to translate requirements into measurable ML solutions and rapidly prototype emerging ML technologies.
Required Skills & Qualifications
3+ years of experience as an ML Engineer, Data Scientist, or Data Engineer focused on building and deploying ML pipelines and models.
Strong proficiency in Python, SQL, and PySpark for large-scale data processing.
Hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
Experience with ML pipeline and model management tools such as MLflow or equivalent.
Experience working with cloud-based environments including AWS, Google Cloud, Azure, or Databricks.
Proven experience managing large datasets with a focus on data quality, scalability, and model training best practices.
Experience with the full ML lifecycle, including experimentation, validation, deployment, monitoring, and model versioning.
Strong software engineering fundamentals with ability to write clean, maintainable, reusable, and well-documented code.
Strong communication and collaboration skills across technical and non-technical teams.
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience.
Preferred Skills:
Experience with healthcare claims, EHR, or life sciences datasets.
Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or a related technical field.
Knowledge of MLOps practices, including CI/CD for ML, model versioning, and deployment.
Experience with deep learning approaches for time series forecasting.
Knowledge of time series forecasting, causal inference, or large language models.
Experience defining success metrics with product managers or analysts.
Experience working in fast-paced Agile environments.
Posted On: 24-09-2026
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.
Summary
Design, build, deploy and maintain scalable production machine learning models and data pipelines for multi-terabyte clinical and consumer datasets. Requires 3+ years building ML pipelines, Python, SQL, PySpark, scikit-learn, PyTorch or TensorFlow, MLflow, and AWS, Azure, Google Cloud or Databricks.
Responsibilities
Design, develop, deploy and maintain production ML models and pipelines in cloud; architect data ingestion, feature engineering for multi-terabyte datasets; manage end-to-end ML lifecycle; collaborate with product and engineering stakeholders
Qualifications
Strong proficiency in Python, SQL, PySpark; scikit-learn, XGBoost, PyTorch or TensorFlow; MLflow; AWS, Google Cloud, Azure or Databricks; large datasets; full ML lifecycle; clean maintainable code; communication skills
Education requirements
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field, or equivalent practical experience
Experience requirements
3+ years as ML Engineer, Data Scientist, or Data Engineer building and deploying ML pipelines and models