Senior Algorithms Engineer — HealthTech ML & Monitoring

Becton Dickinson NA; Irvine (CA); On-site; USD 125,000 - 206,000; Full time

Job summary

Becton, Dickinson and Company in Irvine, California is seeking a Principal Algorithms Engineer to drive the development of advanced algorithms for patient monitoring, applying machine learning and signal processing to transform healthcare.

The role requires a PhD in a relevant field, strong programming in Python or MATLAB, and hands-on experience with deep reinforcement learning, ML/DL, and DSP to quantify performance and support regulatory submissions.

Qualifications

• PhD in electrical engineering, computer science, biomedical engineering, statistics or related field.
• Proficient in Python or MATLAB.
• Strong experience with deep reinforcement learning.
• Strong experience with machine learning and deep learning (CNN, LSTM, Transformer).
• Experience in digital signal processing and mathematical modeling.
• Experience developing algorithms for patient monitoring or biosignal data is a plus.

Responsibilities

• Lead the development of advanced algorithms for patient monitoring using machine learning and signal processing techniques.
• Perform statistical data analyses to characterize algorithm performance.
• Collaborate with clinicians to conduct clinical trials and publish scientific articles.
• Collaborate with cross functional team on regulatory submissions and launching products.

Skills

PhD required

Python

MATLAB

Deep reinforcement learning

Machine learning

Deep learning

Digital signal processing

Mathematical modeling

Algorithm development

Education

PhD in Electrical Engineering / CS / Biomedical Eng / Statistics

Job description

Becton, Dickinson and Company in Irvine, California is seeking a Principal Algorithms Engineer to drive the development of advanced algorithms for patient monitoring, applying machine learning and signal processing to transform healthcare.

The role requires a PhD in a relevant field, strong programming in Python or MATLAB, and hands-on experience with deep reinforcement learning, ML/DL, and DSP to quantify performance and support regulatory submissions.