ML Engineer (US Pharma Data Analytics) - Immediate Joiners

Role Overview

We are seeking a highly skilled

Machine Learning Engineer - US Pharma Data Analytics

to design, develop, deploy, and maintain scalable, production-grade machine learning solutions for pharmaceutical and healthcare analytics. The role focuses 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

that can operate reliably in 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

• At least

3 to 8 years if 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

such as

TensorFlow, PyTorch, or scikit-learn

• Practical exposure to cloud platforms, containerization, and orchestration tools
• Solid understanding of

MLOps methodologies, monitoring, and lifecycle management

• Must have Experience in working with

US based Pharma

data analytics.

Location:

Bangalore

Work Mode:

Hybrid

Shift Timing:

2 PM to 11 PM IST