Machine Learning Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, validate, and optimize machine learning algorithms for biosignal data, encompassing ECG and longitudinal health record data.

• Contribute to the advancement and refinement of the machine learning platform and infrastructure that supports diagnostic and insights capabilities.

• Collaborate with data scientists, software engineers, and clinical experts to convert research innovations into production-ready medical device algorithms.

• Present technical findings to cross-functional stakeholders, executive leadership, and external scientific audiences through publications and conference presentations.

• Utilize machine learning, artificial intelligence, and signal-processing techniques on a substantial labeled ECG dataset to create algorithms that improve diagnostic capabilities and patient outcomes.

• Investigate complex biosignal data, develop and validate new algorithmic interpretation methods, and transform research into scalable healthcare solutions.

• Contribute to the development of next-generation algorithms for analyzing physiological signals derived from wearable and connected health technologies.

⛳️ Requirements

• MS or PhD in Computer Science, Electrical Engineering, Statistics, or a related quantitative discipline.

• Demonstrated experience in machine learning, AI, image/signal processing, or a related field.

• Background in developing algorithms for safety-critical systems, ideally within regulated sectors such as medical devices, healthcare, aerospace, automotive, or robotics.

• In-depth knowledge of machine learning, deep learning, statistical modeling, and time-series analysis.

• Proficient in large-scale self-supervised learning, multimodal foundation models, representation learning, or generative AI techniques.

• Experience in creating and training modern deep learning architectures utilizing frameworks like PyTorch or TensorFlow.

• Strong programming capabilities in Python and familiarity with libraries such as numpy, scikit-learn, pandas, scipy, and related tools.

• Experience handling large datasets and knowledge of database languages such as SQL.

• Experience in developing and deploying machine learning solutions on cloud platforms like AWS, Azure, or GCP.

• Experience in training large-scale deep learning models using distributed multi-node computing environments and optimizing performance for scalability.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.