DigeHealth is pioneering advancements in gastrointestinal health monitoring through cutting-edge wearable technology. As a Machine Learning Engineer, you will play a vital role in developing solutions for patients, researchers and physicians. This position offers an opportunity to use your expertise on impactful health tech innovation, contributing to better clinical outcomes and improved patient care. You will work closely with healthcare professionals, and a dynamic, fast-paced startup team, requiring independence, creativity, and a proactive approach to solving complex challenges.

• Algorithm Refinement: Improve bowel sound recognition algorithms for enhanced accuracy in diverse environments.
• Model Development: Build predictive machine learning models for bowel health events and disorders.
• Sound Processing: Apply audio signal processing techniques like noise reduction and sound classification for gastrointestinal applications.
• Healthcare Collaboration: Work with clinicians to align algorithms with clinical needs and validate their applicability.
• Startup Contribution: Take ownership of tasks and navigate ambiguity in a fast-paced setting.
• Data Management: Ensure quality and usability of large acoustic and contextual datasets.
• Cross-Functional Work: Collaborate with hardware engineers, software developers, and medical advisors to align with device capabilities.
• Documentation: Document methodologies and results, contributing to research publications where applicable.

• Bachelor's or Master’s in Computer Science or related field.
• 2-4 years in Machine learning, with hands-on experience in developing algorithms for computer vision, sound analysis, or audio signal processing.
• Familiarity with healthcare or biomedical applications is a plus.
• Proficiency in Python and frameworks like TensorFlow or PyTorch.
• Experience with large datasets and production-grade machine learning models.
• Expertise in audio signal processing techniques such as denoising and feature extraction.
• Familiarity with predictive analytics and time-series data.
• Experience deploying AI models in real-world products.
• Language: DigeHealth's working language is English. Proficiency in other languages is not required for this role.

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Additional Skills Suggested

• Edge processing and embedded systems deployment.
• Cloud infrastructure experience (AWS, GCP, Azure).
• Familiarity with medical device development and regulatory requirements is a bonus.
• Domain Knowledge: Expertise in computer vision, sound algorithms, and Medical Device Product development including meeting regulatory requirements is highly desirable.

Candidates should apply directly with CV and cover letter to hello@digehealth.care