neko-health - ML Ops Engineer
Requirements
• Production-grade Python fluency: demonstrated experience building and owning end-to-end ML systems in production, not just contributing to them. • ML orchestration ownership: hands-on experience with Dagster or equivalent, including design decisions, not just configuration. • Kubernetes and containerised workload management in a production context. • Infrastructure as Code: Terraform or equivalent, applied to ML infrastructure. • Distributed systems and data pipeline design across multiple data sources or domains. • Experiment tracking and model lifecycle management: MLFlow or equivalent, embedded into team workflows. • Strong communication: able to teach MLOps concepts to Data Scientists and Engineers without an MLOps background, and make architectural recommendations across engineering and science teams. • Experience with PyTorch model serving and inference optimisation at production scale. • Familiarity with Azure ML, AKS, and Blob Storage in an integrated ML platform context. • Prior work in regulated environments: medical devices, ISO 13485, or equivalent. • Exposure to computer vision or sensor data pipelines (skin, cardio, LiDAR, DICOM). • Experience onboarding non-MLOps engineers onto platform tooling.
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.
Benefits
• €100K – €150K • Offers Equity • The successful candidate's actual base compensation will be based upon a variety of factors, including but not limited to work experience, job related knowledge, skills, and professional qualifications. • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here
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