[Urgent Search] Machine Learning Engineer

4 weeks ago


Bangalore Karnataka, India ResMed Full time

About the Team Our innovative Research and Development team is at the forefront of revolutionizing Home Medical Equipment HME Durable Medical Equipment DME out-of-hospital care and home health services Leveraging cutting-edge Artificial Intelligence AI and Machine Learning ML technologies we aim to enhance patient outcomes streamline caregiver workflows and drive efficiency across the continuum of care Our intelligent solutions are designed to empower caregivers and healthcare providers By bridging technology and healthcare we are shaping the future of care delivery ensuring it is smarter more efficient and more impactful About the Role - Lead the design and development of advanced systems for automated data collection curation and ML model training - Write production grade code with proper unit test coverage - Collaborate with cross-functional teams including product UX and engineering to architect ML solutions tailored to the needs of caregivers and home health services - Drive innovation by utilizing the latest deep learning libraries and technologies to develop solutions for predictive analytics workflow optimization and patient care improvement - Mentor and provide technical leadership to ML engineers and data scientists fostering best practices and technical excellence - Build and deploy highly scalable production-ready ML services ensuring reliability and high-quality performance - Research implement and deploy innovative algorithms to address complex healthcare challenges such as risk prediction and personalized care plans - Optimize ML pipelines and ensure their seamless integration into production environments using state-of-the-art deployment tools and practices - Analyze large distributed datasets to uncover actionable insights that improve caregiver workflows and enhance patient care - Ensure models meet healthcare industry standards for explainability fairness and compliance with regulations like HIPAA Let s Talk About You - Education Master s or Bachelor s degree in Computer Science Machine Learning or a related field - Experience - 3 years of hands-on experience in ML model development data pipelines and feature engineering - Strong expertise in Python programming and frameworks like FastAPI pydantic pandas numpy - Good understanding of Test Driven Development - Ability to follow industry standards in Object Oriented Programming software development - Experience with cloud platforms particularly AWS e g SageMaker S3 Lambda DynamoDB API Gateway - Proficient in building CI CD pipelines and deploying scalable solutions with Kubernetes or similar technologies - Expertise in handling and processing large datasets including distributed systems such as Hadoop or Spark - Skills - Advanced understanding of machine learning techniques including deep learning time series analysis and recommendation systems - Ability to design end-to-end ML workflows from data ingestion to production deployment and monitoring - Exceptional problem-solving skills and a passion for leveraging AI to improve home healthcare services What You Can Expect A supportive environment that focuses on people s development and best implementation Opportunity to design influence and be innovative Work with inclusive global teams and the open sharing of new ideas We want your ideas Be supported both inside and outside of the work environment The opportunity to build something meaningful and see a direct positive impact on people s lives Dream big iterate and experiment to drive innovation Joining us is more than saying yes to making the world a healthier place It s discovering a career that s challenging supportive and inspiring Where a culture driven by excellence helps you not only meet your goals but also create new ones We focus on creating a diverse and inclusive culture encouraging individual expression in the workplace and thrive on the innovative ideas this generates If this sounds like the workplace for you apply now We commit to respond to every applicant



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