The job description is comprehensive and detailed, but it can be improved in terms of formatting and clarity. The current structure is somewhat cluttered, especially with the initial paragraph about cookies and data policies, which is irrelevant to the job role. Removing this and organizing the responsibilities, requirements, and benefits more clearly with appropriate HTML tags will enhance readability. Additionally, some repetitive phrases and minor grammatical issues should be corrected for professionalism. Here is a refined version:
Job Title: MLOps Infrastructure Engineer
We are seeking a skilled MLOps Infrastructure Engineer to join our team. The role involves collaborating on architecture, implementing infrastructure components, maintaining documentation, supporting security practices, and working across teams to ensure scalable and efficient MLOps operations.
Responsibilities
* Participate in designing and refining MLOps architecture in collaboration with the architecture team.
* Develop and deploy infrastructure components supporting machine learning operations.
* Create and maintain detailed documentation of system architecture and components.
* Maintain and update configurations for MLOps systems, ensuring security and compliance.
* Support the implementation of security best practices within the MLOps environment.
* Monitor and optimize financial aspects of MLOps infrastructure, including resource usage and costs.
* Evaluate technical solutions and contribute to architectural improvements.
* Assist in decomposing initiatives into technical tasks and managing backlogs.
* Collaborate with engineers, data scientists, and IT teams for consistent MLOps implementation.
* Contribute to continuous process and workflow improvements.
Requirements
* Experience with security practices in technical environments, preferably familiar with Roche SRA/DCR.
* Hands-on experience managing cloud infrastructure costs using FinOps principles.
* Strong understanding of system architecture and design patterns, especially in MLOps.
* Knowledge of MLOps fundamentals such as model serving, pipelines, and monitoring.
* Proficiency in Python for scripting and automation.
* Extensive experience with cloud platforms, preferably AWS.
* Deep familiarity with Docker, Kubernetes, Helm, and Kustomize.
* Practical experience with Infrastructure-as-Code tools like Terraform or AWS CDK.
* Experience with CI/CD tools such as GitLab CI and ArgoCD.
* Knowledge of observability tools like Grafana, ELK, or Datadog.
* Ability to decompose tasks and collaborate effectively across teams.
What We Offer
* Employment on a B2B contract.
* Opportunity to work in a stable, international, and dynamic company.
* Engaging projects with the latest IT technologies.
* Attractive remuneration rates.
* Participation in prestigious international projects.
* Access to Multisport benefits and private healthcare.
Application Process
Interested? Send your CV to topraca@seargin.com.
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Attach CV (PDF/JPG/PNG up to 10MB)*:
I acknowledge that I have read and understood the information clause related to the recruitment process and I confirm my participation. *
I agree to be considered for future recruitment processes conducted by the data controller. *
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