Senior Principal Engineer – Applied ML​/AI Algorithms R&D for Advanced Patient Monitoring

We Are The People Who Give Possibilities Purpose

BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it's no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of Med Tech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

The Applied ML/AI Algorithms team leads the development of advanced algorithms that power BD Advanced Patient Monitoring's next generation of clinically impactful products. We focus on transforming physiological signal data into actionable insights that improve patient monitoring, enable earlier intervention, and drive better outcomes.

This team operates at the intersection of research, product, and clinical translation. We partner closely with engineering, clinical, regulatory, and product teams to bring AI/ML innovations from concept to FDA-cleared, production-grade solutions.

We emphasize rigorous science, practical product thinking, and a shared commitment to improving patient outcomes—accelerating innovation without compromising quality or clinician trust.

We are seeking a Senior Principal Engineer to lead the development and deployment of advanced ML/AI models, including multimodal and foundation-model–inspired approaches, for physiological signal understanding and clinical decision support.

This is a senior individual contributor role with significant technical leadership responsibility. You will drive end-to-end development—from algorithm design and modeling innovation through productionization in regulated environments—translating research-grade models into robust systems that meet real-world clinical constraints and needs.

Beyond individual contributions, you will play a critical leadership role in shaping technical direction, mentoring engineers, and elevating the team's engineering maturity. You will help define and build scalable experimentation pipelines, reproducible workflows, and MLOps practices that accelerate iteration while ensuring rigor and regulatory readiness.

You will partner closely with data, product, and clinical teams to bridge the gap between research and product—building solutions that deliver meaningful, real-world clinical impact.

• Lead the development of AI/ML algorithms from early exploration through production, driving clinically impactful outcomes
• Set technical direction across projects, influencing strategy across modeling, data, and product design
• Translate clinical and product needs into scalable, real-world AI/ML solutions
• Architect solutions that are reliable, efficient, and deployable in regulated, production environments
• Build and scale experimentation and MLOps infrastructure to accelerate team's velocity
• Mentor engineers and elevate the technical bar across the organization
• Partner with clinical, regulatory, and engineering teams to bring AI/ML solutions to market

• PhD with 4 + years or MS with 7 + years or BS with 8+ years of experience in AI/ML, data science, or software engineering
• Experience building and putting into production applied AI, machine learning, LLM/LMM, agentic, or other decision or recommendation systems
• Proven technical leader who can drive ambiguous, high-impact initiatives and influence direction within and across cross-functional teams
• Strong product judgment—able to balance speed, complexity, and real-world impact
• Deep expertise in modern ML/DL/AI frameworks with experience building robust, scalable models for deployment across cloud and/or edge/embedded environments in partnership with systems engineering
• Experience designing robust evaluation frameworks and working with real-world, imperfect data
• Track record of mentoring engineers and shaping engineering practices
• Motivated by applying AI to solve meaningful healthcare problems

• Experience with clinical decision support and physiological or medical time-series data
• Familiarity with clinical workflows or patient monitoring
• Experience with FDA or regulated development environments
• Experien…