Machine Learning Engineer

About the Role

The Digital Product Engineering team at the U.S. Pharmacopeial Convention (USP) is seeking a skilled Machine Learning Engineer. This role is crucial for developing robust Data/ML pipelines, managing large-scale data infrastructure, and enabling advanced analytics capabilities. The position directly supports projects aimed at protecting patient safety and improving global health outcomes.

We are looking for a professional who values clean, accessible, and well-organized data, and who excels at designing systems that empower data scientists, analysts, and business stakeholders to derive actionable insights. The ideal candidate will have a strong passion for data architecture, cloud technologies, and scalable engineering solutions that drive innovation and impact.

How You Will Create Impact at USP

This position is designed to provide a high-level overview of its purpose and critical priorities, with an opportunity to highlight contributions to Diversity, Equity, Inclusion & Belonging initiatives.

• Implement scalable data collection, storage, and processing ML pipelines to meet enterprise-wide data needs.
• Build and optimize data models and data pipelines to support self-service analytics and reporting tools such as Tableau, Looker, and Power BI.
• Collaborate with data scientists to operationalize machine learning models by integrating them into production data pipelines, ensuring scalability and performance.

Who USP is Looking For

The successful candidate will demonstrate an understanding of USP's mission, a commitment to excellence through inclusive and equitable practices, and the ability to build credibility with stakeholders. Key competencies and experience include:

• Building and maintaining data pipelines for structured, semi-structured, and unstructured data.
• Supporting ETL/ELT workflows and data ingestion using batch, streaming, and API-based approaches.
• Developing and optimizing data processing jobs using Python and distributed frameworks.
• Participating in building, training, and deploying machine learning models and data-driven applications.
• Creating dashboards and visualizations to support analytics and business reporting.
• Assisting in deploying data and ML workloads to cloud environments following best practices.
• Collaborating with senior engineers and cross-functional teams to understand requirements and deliver solutions.
• Writing clean, maintainable, and well-documented code; participating in code reviews.
• Continuously learning and applying best practices in data engineering, ML engineering, and MLOps.

Education and Qualifications

• Bachelor’s degree in a relevant field (e.g., Engineering, Analytics or Data Science, Computer Science, Statistics) or equivalent experience.

Additional Desired Preferences

• Strong communication skills (Verbal, written, and interpersonal).
• Introductory knowledge of Generative AI / LLM concepts (prompting, embeddings, RAG basics) is a plus.
• Academic or personal projects involving dashboards, analytics, ML models, or cloud deployments.
• Familiarity with data lakes or warehouses (AWS S3, Redshift, Snowflake, Delta Lake).
• Basic experience building APIs using FastAPI, Flask, or Django.

Supervisory Responsibilities

None

Benefits

USP offers comprehensive benefits to protect you and your family, including company-paid time off, robust healthcare options, and retirement savings plans, ensuring your personal and financial well-being.

USP is proud to be an equal employment opportunity employer (EEOE) and affirmative action employer. We are committed to fostering an inclusive environment where every employee feels empowered and valued, irrespective of background or identity. We are dedicated to working with and providing reasonable accommodation to individuals with disabilities.

Note: USP does not accept unsolicited resumes from third-party recruitment agencies and is not responsible for fees from recruiters or other agencies except under specific written agreement.