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Senior Machine Learning Engineer
Company Overview:
The company behind this opportunity is a global leader in medical equipment manufacturing, pioneering innovative solutions that help people live healthier, higher-quality lives. Their cloud-connected medical devices treat chronic conditions such as sleep apnea and COPD, transforming care and improving patient outcomes. With a commitment to empowering patients, caregivers, and professionals, the company operates across more than 120 countries, supporting out-of-hospital care through advanced software platforms.
Job Description:
Responsibilities:
Build and deliver AI/ML services to various web and mobile applications to drive positive patient outcomes.
Collaborate closely with Data Scientists and Data Engineers to enable faster solution development and deployment, and mentor junior team members.
Build and maintain optimal global AI/ML architectures, providing production support to live AI/ML products.
Understand model performance and ensure proper tracking, logging, and validation for fit-for-purpose models.
Document model and ML system design, experiments, tests, validations, and live metrics.
Develop best practices within and across teams to drive effective outcomes and a progressive mindset.
Identify and implement internal process improvements, automating manual processes, and re-designing infrastructure for scalability.
Handle escalated incidents and suggest solutions to minimize future exposure.
Participate in Code Reviews and process improvements.
Qualifications:
Minimum Qualifications:
5+ years of experience in ML production deployment with a Master’s degree in Data Science, Machine Learning, Computer Science, Software Engineering, or a similar field, or 3+ years with a PhD.
Hands-on experience with building scalable AI/ML systems for continuous training automation, computer vision, natural language processing, or recommender systems.
Experience with AWS or other cloud-based tools for data pipelining, model development, deployment, monitoring, and MLOps tools such as SageMaker, Airflow, Kubeflow, etc.
Strong grounding in machine learning techniques, including regression methods, classification, performance evaluation, unsupervised learning, reinforcement learning, and optimization.
Experience with big data tools such as EMR, Spark, or similar.
Proficiency with relational SQL and NoSQL databases.
Experience with developing production-grade Python code.
Preferred Qualifications:
Experience with large-scale AI/ML problems, including continuous training, computer vision, and recommender systems.
Ability to design innovative solutions that drive high-value outcomes for patients and customers.
Disclaimer:
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore during these challenging times.
No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
No Client Relationship: This company is not a client of SpringCube unless stated.
Users must click to apply, redirecting to the employer’s career page.
No Liability: SpringCube is not liable for inaccuracies.
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