Machine Learning Engineer

Kos is transforming health monitoring through cutting-edge wearable technology and artificial intelligence. Our flagship product, Argus, is a wristband that enables non-invasive blood glucose monitoring through continuous, personalized data collection. Combined with our proprietary AI assistant that learns from medical, health, and wellbeing literature and knowledge bases, we provide real-time, interactive, and cost-effective monitoring solutions. Our platform delivers personalized insights, proactive alerts, and data-driven guidance to help users understand and manage their health and wellbeing.Position overviewWe're seeking a talented Machine Learning Engineer to join our team and build the predictive models at the core of our health monitoring platform. You'll develop and optimize machine learning systems for non-invasive blood glucose prediction and monitoring, working with continuous data streams from our Argus wristband. This is an opportunity to apply cutting-edge ML techniques to challenging real-world problems in health monitoring and make a meaningful impact on how people understand and manage their wellbeing.ResponsibilitiesDesign, develop, and deploy machine learning models for blood glucose prediction and health monitoringBuild and refine algorithms that process continuous physiological data from wearable devicesDevelop personalized prediction models that adapt to individual user patterns and behaviorsCollaborate with firmware engineers, backend engineers, and mobile engineers to integrate ML models into production systemsCreate robust data pipelines for training, validation, and real-time inference at scaleResearch and implement state-of-the-art ML techniques for time-series analysis and physiological signal processingOptimize model accuracy, latency, and resource utilization for deployment on cloud infrastructureMonitor model performance in production and iterate based on real-world data and feedbackWrite clean, maintainable code and comprehensive documentationStay current with the latest developments in machine learning and health monitoring technologiesRequired QualificationsBachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related field (or equivalent practical experience)Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)Understanding of machine learning fundamentals including supervised/unsupervised learning, neural networks, and model evaluationExperience with data processing and analysis using libraries like pandas, NumPy, and SQLKnowledge of software engineering best practices including version control (Git), testing, and CI/CDStrong problem-solving and analytical skillsExcellent communication and collaboration abilitiesPassion for applying ML to solve real-world problems that help peoplePreferred QualificationsExperience with time-series analysis, forecasting, or signal processingBackground in physiological data analysis or health monitoring applicationsKnowledge of personalization algorithms and adaptive learning systemsExperience with natural language processing or working with large language modelsFamiliarity with MLOps practices and tools for model deployment and monitoringUnderstanding of cloud platforms (AWS, Google Cloud, Azure) and containerizationExperience with anomaly detection or predictive alerting systemsKnowledge of wearable technology, IoT devices, or biosensor dataPublications or contributions to ML research or open-source projectsExperience in early-stage startups or fast-paced environmentsWhat We OfferCompetitive pay and equity in a fast-growing health tech startupComprehensive health benefits and 401(k)Daily lunch and plenty of office perksA collaborative team working on AI with real healthcare impactEqual OpportunityKos is committed to creating a diverse and inclusive workplace. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of race, color, religion, sex, national origin, age, disability, or any other protected characteristic.Application ProcessPlease submit:Resume highlighting machine learning projects and academic achievements.Cover letter describing your passion for AI and interest in healthcare applications.Portfolio of ML projects (GitHub, Kaggle, or research papers).Combine everything in one file. Applications with missing elements will be disregarded. recblid 2pm70h7lt4j9ky0yv70oeoqrfxdoia