Informacje o stanowisku

technologies-expected :

• Python
• Kubernetes
• Terraform

• AWS

• Platform Architecture & Engineering
• Design, implement, and own large-scale cloud-based HPC and MLOps platforms supporting AI model training, genomic sequencing, and precision medicine.
• Architect multi-environment clusters (AWS, GCP, Azure), enabling GPU/FPGA workloads and advanced observability.
• Lead the development of developer and cloud platforms, including internal engineering accelerators and reusable toolsets.
• Platform Catalog & Developer Experience
• Design, implement, and manage unified platform catalogs using Backstage, enhancing developer experience and application metadata management.
• Develop custom plugins and APIs for Backstage to support internal engineering workflows and documentation.
• Automation & DevOps Excellence
• Build and maintain Python-based automation frameworks, CI/CD pipelines, and Infrastructure-as-Code (Terraform, Helm, Pulumi, AWS CDK).
• Operationalize containerized solutions using Docker and Kubernetes, integrating MLflow, Kubeflow, and other orchestration platforms.
• Implement robust automation for provisioning, configuring, and managing cloud resources across multiple environments.
• MLOps & Reliability Engineering
• Lead the implementation of Service Level Indicators (SLIs), Service Level Objectives (SLOs), and advanced observability (Prometheus, Grafana, PagerDuty).
• Develop and maintain APIs and services for model management, feature stores, and inference pipelines.
• Operationalize ML model serving at scale using frameworks such as TensorFlow Serving, TorchServe, KServe, and Seldon Core.
• Ensure compliance with industry standards (e.g., HIPAA, FDA) for data protection and reliability.
• Collaboration & Leadership
• Mentor engineers and lead cross-functional teams to deliver integrated solutions.
• Champion engineering excellence through design documentation, code reviews, and testing automation.
• Present at industry summits, author technical proposals, and contribute to open-source projects (Kubernetes, Helm, Go, Envoy).
• Continuous Improvement
• Drive agile delivery, sprint planning, and performance optimization.
• Lead incident response and disaster recovery initiatives for mission-critical platforms.
• Foster a culture of shared ownership, transparency, and innovation

• 7+ years of hands-on software engineering experience in cloud infrastructure, DevOps, and MLOps.
• Deep expertise in Python, Kubernetes, Terraform, Helm, and CI/CD pipeline development.
• Proven experience architecting and operating containerized solutions on AWS, GCP, and Azure.
• Strong knowledge of Infrastructure-as-Code, distributed systems, and production system reliability.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

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