About the Company

The U.S. Pharmacopeial Convention (USP) is an independent scientific organization dedicated to improving global public health by establishing quality standards for medicines, dietary supplements, and food ingredients. With a strong mission to ensure safe and high-quality healthcare products worldwide, USP collaborates with leading experts in science and health across multiple global locations.

Introduction

USP’s Digital Product Engineering team is seeking a Machine Learning Engineer to build and maintain robust data and machine learning pipelines. This role focuses on managing large-scale data infrastructure and enabling advanced analytics capabilities to support enterprise-wide initiatives.

As an ML Engineer, you will play a key role in designing scalable data systems, supporting data scientists, and ensuring that machine learning models are efficiently deployed and integrated into production environments.

Key Responsibilities

Technical Development

Implement scalable data collection, storage, and processing pipelines for enterprise data needs.
Build and optimize data models and pipelines to support analytics and reporting tools.
Develop and maintain data pipelines for structured, semi-structured, and unstructured data.
Design and optimize data processing jobs using Python and distributed frameworks.

Execution & Problem Solving

Support ETL/ELT workflows using batch, streaming, and API-based data ingestion.
Collaborate with data scientists to operationalize machine learning models.
Ensure scalability, performance, and reliability of ML pipelines and data systems.
Assist in deploying data and ML workloads to cloud environments following best practices.

Growth & Collaboration

Work closely with cross-functional teams including data scientists, analysts, and stakeholders.
Create dashboards and visualizations using tools like Tableau, Looker, or Power BI.
Participate in code reviews and maintain high-quality documentation standards.
Continuously learn and apply best practices in data engineering, ML engineering, and MLOps.

Required Qualifications

Strong proficiency in Python for data engineering and machine learning tasks.
Experience building and maintaining data pipelines for various data types.
Understanding of ETL/ELT processes and data ingestion techniques.
Knowledge of distributed data processing frameworks.
Familiarity with machine learning model development and deployment.
Experience with cloud platforms and data infrastructure.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.

Preferred Qualifications

Experience with analytics and visualization tools such as Tableau, Looker, or Power BI.
Knowledge of MLOps practices and tools.
Familiarity with large-scale data architectures and optimization techniques.
Experience working in cross-functional and global teams.

Why Join Us / Benefits

At USP, you will contribute to a mission-driven organization that impacts global healthcare quality. The role offers an opportunity to work on cutting-edge data and machine learning systems while collaborating with experts across domains.

Work on impactful projects that improve global health outcomes.
Collaborative and inclusive work environment.
Opportunities for continuous learning and professional growth.
Exposure to advanced data engineering and ML technologies.
Be part of a globally recognized scientific organization.