Posted Apr 29, 2026
As a Machine Learning Engineer specialized in US Pharma Data Analytics, your role involves designing, developing, deploying, and maintaining scalable machine learning solutions for pharmaceutical and healthcare analytics. Your primary focus will be on transforming complex healthcare datasets into reliable ML-driven insights while ensuring robustness, scalability, and regulatory compliance in real-world environments. Key Responsibilities:
Required Skills & Experience:
3 to 8 years of strong experience in Machine Learning model development and deployment
Hands-on experience with production ML systems and scalable data pipelines
Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or scikit-learn
Practical exposure to cloud platforms, containerization, and orchestration tools
Solid understanding of MLOps methodologies, monitoring, and lifecycle management
Experience in working with US based Pharma data analytics Location: Bangalore Work Mode: Hybrid Shift Timing: 2 PM to 11 PM IST As a Machine Learning Engineer specialized in US Pharma Data Analytics, your role involves designing, developing, deploying, and maintaining scalable machine learning solutions for pharmaceutical and healthcare analytics. Your primary focus will be on transforming complex healthcare datasets into reliable ML-driven insights while ensuring robustness, scalability, and regulatory compliance in real-world environments. Key Responsibilities:
Design, build, and deploy end-to-end machine learning solutions for production environments
Translate data science prototypes into scalable, efficient, and maintainable ML systems
Develop and manage large-scale data processing pipelines for structured and unstructured pharma and healthcare data
Optimize model performance through feature engineering, hyperparameter tuning, and architecture improvements
Implement robust monitoring frameworks to track model accuracy, drift, performance degradation, and system health
Ensure high availability, fault tolerance, and scalability of ML systems in production
Collaborate closely with Data Scientists to operationalize analytical and predictive models
Work alongside Data Engineers to ensure efficient data ingestion, transformation, and storage pipelines
Apply industry-standard MLOps practices including CI/CD pipelines, automated testing, model versioning, and reproducible experimentation
Maintain documentation and ensure compliance with data governance, security, and healthcare regulations
Continuously evaluate emerging tools, frameworks, and best practices to improve machine learning workflows
Required Skills & Experience:
Don't want to apply yourself?
Our team writes your resume, applies for you, preps you for interviews, and negotiates your offer.
Browse Jobs
By Role
By City