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MLOps / Technical Lead @ Square One Resources

MLOps / Technical Lead @ Square One Resources

Square One ResourcesRemote, Czech Republic
Před 16 dny
Popis pozice

Project Description :

We are seeking a highly skilled  MLOps / Technical Lead to support a complex and evolving Machine Learning Operations environment. The position requires hands-on involvement in technical architecture, security processes, cloud cost optimization (FinOps), and guiding the engineering team in best practices for scalable and secure MLOps infrastructure. The ideal candidate will be responsible for driving technology decisions, conducting technical evaluations, and coordinating the implementation of robust ML solutions in a cloud-native environment.

Must-Have Technologies :

  • Python
  • AWS  (preferred) or other cloud platforms
  • Docker & Kubernetes , including  Helm  and  Kustomize
  • Infrastructure as Code :  Terraform and / or AWS CDK
  • CI / CD Tools :  GitLab CI, ArgoCD

Qualifications : Security

  • Practical experience with implementing and managing security processes in a cloud environment.
  • FinOps

  • Hands-on experience in monitoring, optimizing, and reporting cloud infrastructure costs.
  • Architecture & Technical Knowledge

  • Strong understanding of system architecture and design patterns.
  • Experience in MLOps or adjacent fields involving ML pipeline orchestration, model serving, monitoring, and data processing.
  • Technical Proficiency

  • Advanced Python programming skills.
  • Deep experience with cloud platforms (preferably AWS).
  • Proficient in Docker and Kubernetes (including Helm / Kustomize).
  • Experience with Infrastructure-as-Code using Terraform or AWS CDK.
  • Familiarity with CI / CD pipelines (GitLab CI, ArgoCD).
  • Exposure to observability tools such as the  Grafana Stack ,  ELK , or  Datadog .
  • Experience with MLOps platforms like  Kubeflow ,  KServe  is a strong plus.
  • Task Management & Cross-functional Collaboration

  • Demonstrated experience in breaking down complex tasks and delivering actionable work plans.
  • Ability to coordinate with cross-functional teams and drive collaborative success.
  • Project Description :

    We are seeking a highly skilled  MLOps / Technical Lead to support a complex and evolving Machine Learning Operations environment. The position requires hands-on involvement in technical architecture, security processes, cloud cost optimization (FinOps), and guiding the engineering team in best practices for scalable and secure MLOps infrastructure. The ideal candidate will be responsible for driving technology decisions, conducting technical evaluations, and coordinating the implementation of robust ML solutions in a cloud-native environment.

    Contribute to the design, development, and maintenance of MLOps infrastructure and solutions., Define and implement architectural standards and best practices., Prepare and maintain system architecture documentation., Participate in hands-on engineering tasks related to infrastructure and MLOps pipelines., Lead the execution of Proofs of Concept (PoCs) for emerging technologies., Assess technical solutions and make data-driven recommendations for implementation., Assist the team in decomposing tasks and epics into manageable components., Identify and manage dependencies across technical initiatives., Recommend optimal implementation strategies and approaches., Lead Security Risk Assessments (SRA) and Data Classification Requests (DCR)., Coordinate with stakeholders on security audits and implement remediation plans., Monitor and optimize cloud resource usage and associated costs., Develop and manage budget plans for MLOps infrastructure and tooling., Provide transparent and accurate cost analysis and reporting.] Requirements : Python, AWS, Cloud platform, Kubernetes, Helm, Kustomize, Infrastructure as Code, AWS CDK, CD tools, ArgoCD, Security, Cloud, Design Patterns, MLOps, Grafana, ELK Stack, Datadog, Kubeflow, Docker, Terraform, CD pipelines Additionally : Remote work.

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    Technical Square One • Remote, Czech Republic