neko-health - ML Ops Engineer
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Requirements
• Strong programming skills in Python with solid understanding of Machine Learning concepts. • Experience building end-to-end production ML systems and platformization initiatives. • Knowledge of PyTorch, Kubernetes, Terraform, distributed systems, and ML orchestration tools. • Advanced understanding of production Machine Learning tools and best practices. • Ability to operate within complex ecosystems spanning medical domain, regulatory requirements, hardware, firmware, and sensor data. • Strong judgment navigating evolving tooling landscapes and applying the right solutions to real-world problems.
Responsibilities
• Build reusable and scalable components supporting Machine Learning operations and platformization. • Own and maintain Machine Learning systems and platform services. • Establish and promote best practices across experiment tracking, model lifecycle, and evaluation. • Design and maintain production inference workflows delivering reliable and timely outputs. • Collaborate cross-functionally with Clinical Researchers, Data Scientists, ML Engineers, and Data Engineers. • Ensure ML systems and workflows align with healthcare and data privacy requirements.
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