Associate Engineer, Analytical AI Engineering

Associate Engineer, Analytical AI EngineeringAt Bristol Myers Squibb, our employees often ask, "Who are you working for?"—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.The Associate Engineer is a developing individual contributor who delivers reliable, well-scoped engineering work within established patterns. You will help build data pipelines, ML workflow components, and platform features that support production-ready AI/ML solutions. You will build technical proficiency, contribute consistently against team commitments, and work within proven architecture patterns with guidance from senior engineers after initial alignment. This role is well suited for early-career engineers who are ready to take on real ownership while building toward increasingly independent delivery. The ideal candidate is dependable, curious, and eager to grow.Key ResponsibilitiesTechnical Delivery - Implement data pipelines, ML workflow components, and platform features following established architecture patterns and coding standards. Write readable, maintainable, testable code with limited guidance after initial design alignment with senior engineers. Deliver well-scoped work reliably and on schedule; understand how your work fits into the larger solution.Problem Solving - Write and maintain tests for your work; ensure changes are tested before deployment. Troubleshoot issues within your assigned pipelines and features with minimal guidance; identify root causes and propose solutions. Navigate the codebase and data designs with growing independence after initial orientation.Collaboration & Growth - Contribute input to team scoping and design exercises; share observations that improve how the team approaches recurring problems. Explain your work clearly to teammates, including what you built, why, and any trade-offs. Demonstrate awareness of the business context for your work and how it connects to the team's broader goals. Take ownership of your development; actively seek feedback and apply it to strengthen your technical and professional skills.QualificationsEducation - BA/BS required (quantitative or engineering discipline preferred). Experience - 0-2 years of experience in data engineering, software engineering, ML engineering, or a related field; relevant advanced degrees contribute to required years of experience. Technical Skills - Proficiency in Python and SQL; familiarity with data pipeline development and common processing patterns. Working knowledge of version control (Git), testing practices, code review, and documentation. Exposure to cloud environments (AWS, Azure, or Databricks); willingness to develop deeper platform proficiency. Familiarity with ML concepts and workflows (model training, feature engineering, data preparation); MLOps experience a plus.Competencies - Works effectively within team guidelines and standards. Builds positive working relationships with teammates and cross-functional partners. Reliable: delivers commitments and communicates proactively when blockers arise. Demonstrates curiosity and commitment to growing technical and professional skills.We hire for skills and capabilities, not just credentials – if this role excites you, but doesn't perfectly match your resume, we encourage you to apply anyway.