ML Engineer

About the job

Description Who is USP? The U.S. Pharmacopeial Convention (USP) USP is an independent scientific organization that collaborates with the world's top experts in health and science to develop quality standards for medicines, dietary supplements, and food ingredients. USP's fundamental belief that Equity = Excellence manifests in our core value of Passion for Quality through our more than 1,100 talented professionals across five global locations to deliver the mission to strengthen the supply of safe, quality medicines and supplements worldwide. Brief Job Overview The Digital product engineering team at USP is seeking a ML Engineer with expertise in building robust Data/ML pipelines, managing large-scale data infrastructure, and enabling advanced analytics capabilities. This role is critical to supporting projects that align with our mission to protect patient safety and improve the health of people around the world. We are looking for a professional who understands the value of clean, accessible, and well-organized data, and who enjoys designing systems that empower data scientists, analysts, and business stakeholders to derive actionable insights. How will YOU create impact here at USP? The position's purpose should provide a high-level overview of why the position exists and briefly identify the most critical priorities of the position. This is an opportunity to highlight any features or duties of the role related explicitly to the Diversity, Equity, Inclusion & Belonging work of the Department. • Implement scalable data collection, storage, and processing ML pipelines to support 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 and ensuring scalability and performance. Who USP is Looking For? The Successful Candidate Will Have a Demonstrated Understanding Of Our Mission, Commitment To Excellence Through Inclusive And Equitable Behaviors And Practices, Ability To Quickly Build Credibility With Stakeholders, Along With The Following Competencies And Experience • Build and maintain data pipelines for structured, semi‑structured, and unstructured data. • Support ETL/ELT workflows and data ingestion using batch, streaming, and API‑based approaches. • Develop and optimize data processing jobs using Python and distributed frameworks. • Participate in building, training, and deploying machine learning models and data‑driven applications. • Create dashboards and visualizations to support analytics and business reporting. • Assist in deploying data and ML workloads to cloud environments following best practices. • Collaborate with senior engineers and cross‑functional teams to understand requirements and deliver solutions. • Write clean, maintainable, and well‑documented code; participate in code reviews. • Continuously learn and apply best practices in data engineering, ML engineering, and MLOps. Education Bachelor’s degree in relevant field (e.g. Engineering, Analytics or Data Science, Computer Science, Statistics) or equivalent experience.