Staff Machine Learning Engineer

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 MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

As a Staff Machine Learning Engineer, you will lead the design, development, and deployment of machine learning solutions that power AI-driven decision-making across the BD Connected Care portfolio. You will build and operationalize models for forecasting, optimization, anomaly detection, and other advanced analytics use cases, transforming high-quality data into scalable, intelligent products.

This is a hands-on technical leadership role where you will own the end-to-end machine learning lifecycle, from experimentation and model development to deployment, monitoring, and continuous improvement. You will help define the architecture, engineering standards, and best practices that shape the future of BD's AI platform while collaborating across engineering, product, and clinical teams to deliver impactful solutions.

The ideal candidate combines deep machine learning expertise with strong software engineering skills, takes ownership of complex technical challenges, and is motivated by BD's mission to improve patient outcomes through innovation and AI.

• →Bachelor's in Machine Learning, Statistics, Operations Research, Applied Math, Computer Science, or related field. 

• →7+ years of hands-on ML/AI and software engineering with production ownership, including delivery of forecasting and/or optimization systems in production. 

• →Deep expertise in model development and training across both classical ML and deep learning, including time-series and hierarchical or multi-series settings. 

• →Excellent Python; fluent with NumPy, pandas, scikit-learn, statsmodels, PyTorch, and a forecasting stack (Prophet, GluonTS, Nixtla, or PyTorch Forecasting). 

• →Track record of moving models from research code into production environments, beyond notebooks and prototypes, including 3+ years building ML services on AWS without relying on SageMaker as the primary ML platform. Comfortable with Docker, Kubernetes-based deployment, and GitHub Actions CI/CD. 

• →Strong software-engineering habits: testing, packaging, CI, code review, observability.  
• →Working in Agile/Scrum and documenting in Confluence. 

We are building a high-ownership, mission-driven team, energized by the opportunity to solve hard problems that make a difference in patients' lives. 

• High ownership - You take full responsibility for outcomes. You identify problems early and drive them to resolution, taking initiative rather than waiting for direction. 

• Entrepreneurial spirit - You think and act like an owner: resourceful, creative, willing to challenge assumptions, and consistently focused on impact. You find practical paths forward through difficult problems. 

• Mission-driven work ethic - You are motivated by the work we are doing to advance the world of health and improve patient outcomes, and you bring genuine energy and commitment to that mission. You are driven by a real sense of purpose in your work. 

• Creative problem-solving - You are comfortable working through ambiguity. You dig in, experiment, iterate, and deliver, and you are energized by the challenge of figuring things out and finding the right solution. 

• AI-native mindset - You actively use the latest AI tools to accelerate your own work across coding, research, design, and documentation, and you are eager to keep advancing what is possible with AI in your craft.