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ML Platform Engineer
Resumo da oferta
A technology solutions provider in Singapore is seeking a skilled ML Platform Engineer responsible for automating and maintaining machine learning platform infrastructure. Applicants should have substantial experience with CDSW, Docker, Kubernetes, and Python, alongside strong MLOps knowledge. The role involves managing deployment processes and ensuring infrastructure reliability.
Qualificações
- 4+ years of relevant working experience.
- Hands-on experience with CDSW or similar ML/AI platforms.
- Experience in deploying, monitoring, and maintaining ML infrastructure.
Responsabilidades
- Automate deployment and management processes for machine learning platforms.
- Develop and maintain documentation for platform configurations.
- Troubleshoot and resolve platform issues.
Conhecimentos
Ferramentas
We are seeking a skilled ML Platform Engineer, responsible for automating, deploying, patching, and maintaining our machine learning platform infrastructure. You need to have hands‑on experience with Cloudera Data Science Workbench (CDSW), Cloudera Data Platform (CDP), Docker, Kubernetes, Python, Ansible, GitLab, and MLOps best practices.
- Automate deployment and management processes for machine learning platforms using tools such as Ansible and Python.
- Deploy, monitor, and patch ML platform components, including Cloudera Data Science Workbench (CDSW), Docker containers, and Kubernetes clusters.
- Ensure high availability and reliability of ML infrastructure through proactive maintenance and regular updates.
- Develop and maintain comprehensive documentation for platform configurations, processes, and procedures.
- Troubleshoot and resolve platform issues, ensuring minimal downtime and optimal performance.
- Implement best practices for security, scalability, and automation within the ML platform ecosystem.
- 4+ years of relevant working experience.
- DevOps / Platform Engineers with Cloudera or Azure, along with Python and ML.
- Hands‑on experience with CDSW (Cloudera Data Science Workbench) or similar ML/AI platforms.
- Strong expertise in containerization and orchestration using Docker and Kubernetes (AKS preferred).
- Proficiency in Python programming (enterprise‑level applications, automation, and scripting).
- Experience with Ansible for infrastructure as code (IaC), deployment automation, and configuration management.
- Strong knowledge of Unix/Linux systems (administration, troubleshooting, performance tuning).
- Practical experience with GitLab for source control and CI/CD pipeline automation.
- Deep understanding of MLOps principles and best practices (deployment, monitoring, lifecycle management of ML workloads).
- Experience in designing, developing, and maintaining distributed systems and services.
- Proven ability in patching, updating, and maintaining platform infrastructure.
- Previous banking domain experience.
- Familiarity with Cloudera CDP ecosystem (beyond CDSW).
- Knowledge of monitoring & observability tools (Prometheus, Grafana, ELK).
- Exposure to Airflow, MLflow, or Kubeflow for workflow and ML lifecycle orchestration.
- Cloud platform experience with Azure (AKS, networking, storage, monitoring).
* O salário de referência é obtido com base em objetivos de salário para líderes de mercado de cada segmento de setor. Serve como orientação para ajudar os utilizadores Premium na avaliação de ofertas de emprego e na negociação de salários. O salário de referência não é indicado diretamente pela empresa e pode ser significativamente superior ou inferior.