4 дня назад
Senior Platform Engineer - ML Ops (MLOps)
65 600 - 98 400€
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Platform Engineer - ML Ops (MLOps) (cloud/MLOps): Building shared platform services and machine learning operations capabilities for connected cardiac-care software with an accent on cloud-native systems, automation, CI/CD, and production ML lifecycle management. Focus on designing reusable APIs and infrastructure, deploying and monitoring models, improving reliability and observability, and solving complex distributed-system issues.
Location: Galway, County Galway, Ireland; hybrid work
Salary: €65,600–€98,400 per year, plus eligibility for the Incentive Plan.
Company
develops healthcare technologies, including connected cardiac-care systems that support implantable medical devices and clinical decision-making.
What you will do
- Design, implement, and operate shared platform and MLOps capabilities that improve software delivery, developer productivity, and operational efficiency.
- Build reusable services, APIs, automation, CI/CD pipelines, infrastructure-as-code templates, and self-service engineering capabilities.
- Support the full machine learning lifecycle, including model development, training, validation, deployment, monitoring, versioning, reproducibility, and ongoing operations.
- Improve platform reliability, security, observability, performance, scalability, maintainability, and cost effectiveness.
- Investigate complex technical issues, lead root-cause analysis, and implement production improvements across multiple systems.
- Partner with software engineers, ML engineers, data scientists, architects, security specialists, and infrastructure teams while providing technical guidance and mentoring.
Requirements
- Bachelor's degree in a relevant technical discipline and at least 4 years of relevant experience, or an advanced degree and at least 2 years of relevant experience.
- Experience designing, developing, deploying, and operating cloud-native or distributed software systems in production.
- Experience developing platform services, APIs, CI/CD pipelines, automation solutions, infrastructure as code, or shared engineering capabilities.
- Strong production software development experience with Python.
- Experience supporting machine learning development and deployment workflows, including model training, validation, deployment, monitoring, versioning, and lifecycle management.
- Experience troubleshooting complex technical issues, performing root-cause analysis, and improving system reliability.
Nice to have
- Experience running, deploying, and monitoring machine learning models in production.
- Experience with Docker, Kubernetes, and Helm.
- Experience with AWS, Microsoft Azure, or Google Cloud Platform.
- Experience with Apache Kafka or similar event-streaming technologies.
- Experience with Dynatrace, ELK Stack, Prometheus, Grafana, or comparable observability tools.
Culture & Benefits
- Hybrid work arrangement.
- Competitive salary and flexible benefits package.
- Benefits and resources designed to support employees across career and life stages.
- Work focused on secure, reliable, and innovative medical technologies serving patients worldwide.
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