Remote Algorithms and Machine Learning Engineer III/IV

Description:

• Work as a Machine Learning Engineer in Beacon Biosignals' analytics and machine learning domain.
• Collaborate with data scientists, neuroscientists, engineers, and clinicians to develop machine and deep learning models for analyzing brain and biosignal data.
• Focus on advancing sleep, neurological, and psychiatric therapy development.
• Contribute to the entire biosignal-based algorithm development lifecycle for medical devices.
• Select and implement appropriate methods for problem-solving, including deep learning techniques.
• Enhance internal deep learning and machine learning tools to improve team efficiency and encourage rapid experimentation.
• Ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested.
• Present results to key stakeholders and assist in utilizing algorithms for client engagement.
• Participate in client-facing projects to understand and shape the impact of Beacon algorithms for customers.

Requirements:

• Several years of industry experience in machine learning and deep learning, especially in health sciences or regulated fields.
• Familiarity with digital signal processing (DSP) and statistics.
• Proficiency in PyTorch or other deep learning frameworks for training, developing, and deploying models.
• Knowledge of best practices in software and ML engineering, including testing, version control, code reviews, and documentation.
• Familiarity with biosignals, medical imaging data, or large time-series datasets.
• Ability to collaborate effectively in a team environment and communicate complex technical topics clearly.
• Excitement to participate in the entire algorithm development lifecycle and work with clients benefiting from the algorithms.
• Excellent English written, verbal, and listening skills.

Benefits:

• Opportunity to work remotely with a first-class remote work experience.
• Chance to work alongside a diverse team of professionals in the field.
• Access to in-person office hubs in Boston, New York City, and Paris.
• Contribution to advancing sleep, neurological, and psychiatric therapy development.
• Continuous learning and growth in the domain of machine learning and deep learning.