Staff Machine Learning Engineer

BD is hiring a Staff Machine Learning Engineer to help build clinically meaningful AI and ML for continuous physiological monitoring, disease detection, and predictive clinical decision support. This onsite role in Laguna Canyon, CA focuses on end-to-end development and deployment across both cloud environments and edge medical devices, leveraging multi-modal healthcare data to support safer, more effective patient monitoring.

Responsibilities

• Lead the design, development, validation, and deployment of AI/ML algorithms for continuous physiological monitoring, including novel vital sign development, disease detection, risk stratification, and early warning systems.
• Develop algorithms using multi-modal data sources such as physiological waveforms and time-series signals (for example, PPG, blood pressure, capnography, and other monitoring signals), bedside and wearable sensor data, and electronic health records and structured clinical data.
• Translate clinical and physiological understanding into robust algorithm design, including feature selection, model architecture, performance targets, and clinically interpretable outputs.
• Build end-to-end algorithm pipelines covering data ingestion, signal quality assessment, annotation, feature extraction, model training, validation, robustness testing, and post-market performance monitoring where applicable.
• Partner with clinical, medical affairs, regulatory, quality, and product teams to ensure appropriate clinical context, usability, safety, and regulatory considerations.
• Develop and optimize algorithms for cloud and for edge or embedded medical devices, accounting for latency, memory, compute, power, cybersecurity, and reliability constraints.
• Support verification, validation, documentation, risk analysis, and design controls for regulated medical technology products.
• Contribute to intellectual property generation, technical strategy, research roadmaps, and external scientific engagement.

Requirements

• 7+ years of industry experience in AI/ML, algorithm development, biomedical signal processing, healthcare analytics, medical devices, or a related technical area.
• Master’s or PhD degree preferred in Electrical Engineering, Biomedical Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Computational Biology, or a related engineering or quantitative field.
• Deep expertise in machine learning and AI model development, including both classical and modern approaches.
• Strong hands-on experience with physiological time-series data, biomedical signals, medical device data, or clinical datasets.
• Understanding of human physiology as it relates to patient monitoring.
• Demonstrated experience taking algorithms from early feasibility through productization or deployment.
• Experience with multi-modal healthcare data, such as sensor signals, EHR data, imaging data, lab data, and clinical outcomes.
• Strong programming skills in Python and experience with ML/AI frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent tools.
• Experience with cloud-based algorithm development and deployment on platforms such as Azure, AWS, or GCP.
• Experience optimizing models for constrained environments, including embedded systems, edge devices, or near-real-time medical technology platforms.
• Strong understanding of model evaluation including sensitivity, specificity, AUROC, calibration, false alarm burden, clinical utility, robustness, and generalizability.
• Excellent communication skills, able to explain complex technical concepts to engineering, clinical, regulatory, and business stakeholders.

Preferred Qualifications

• Experience developing AI/ML algorithms for regulated medical devices, digital health products, clinical decision support tools, or Software as a Medical Device (SaMD).
• Familiarity with medical device development practices, including design controls, risk management, verification and validation, human factors, clinical performance evaluation, and regulatory documentation.
• Experience with signal quality assessment, artifact detection, missing-data handling, sensor fusion, uncertainty quantification, and explainable AI.
• Familiarity with MLOps and model lifecycle management, version control, data governance, automated testing, and post-deployment monitoring.

Tech Stack

Python, PyTorch, TensorFlow, scikit-learn, Azure, AWS, GCP, Transformer-based models, foundation-model approaches.

Benefits

• Medical, dental, vision, health savings and flexible spending accounts
• Life and disability insurance
• Wellness resources and mental health support
• Disease management programs
• 401(k), deferred compensation programs, and financial counseling
• DailyPay
• Educational savings resources and educational assistance
• Paid time off, company holidays, and commuter benefits
• Parental leave, adoption assistance, backup care, caregiving support, and employee assistance programs
• Caregiving and family support options including family and medical leave
• Pet insurance, legal services, associate discount programs
• Bereavement leave, military leave, personal leave, and jury duty leave

Location: USA CA - Irvine Laguna Canyon (onsite)

Salary range: $129,600 - $207,400 USD annually