Senior Machine Learning Engineer

Salary

Core Qualifications

Preferred Qualifications

Key Responsibilities

• •Improve existing production machine learning models through systematic error analysis, improved data, targeted experimentation, and changes to model architectures and training approaches.
• •Develop machine learning models for new products, taking problems from initial formulation and feasibility experiments through training, validation, and production integration.
• •Collaborate with clinicians and product stakeholders to define meaningful evaluation criteria, including sensitivity, specificity, and the clinical implications of different error types.
• •Evaluate model robustness across patient populations, clinical sites, imaging equipment, and acquisition conditions, identifying performance gaps and generating evidence that improvements generalize effectively.
• •Improve data curation and annotation workflows by addressing coverage gaps, label quality, and potential sources of data leakage.
• •Build reproducible training and evaluation pipelines with traceable datasets, experiments, and model versions.
• •Partner with software engineers to optimize inference performance, resource consumption, and operational reliability, while investigating model issues that arise in production.
• •Research relevant scientific developments, test promising approaches, and make evidence-based decisions about technologies and methodologies to adopt.
• •Contribute to model validation and technical documentation in collaboration with quality and regulatory teams.
• •Review code and experiments, provide constructive technical feedback, mentor colleagues, and communicate technical findings, risks, and trade-offs clearly.
• •Follow applicable data privacy, compliance, safety, confidentiality, quality, and regulatory standards throughout the development and delivery lifecycle.
• •Maintain a professional, collaborative, and accountable approach while adapting to new technologies, methods, systems, and responsibilities.