Looking for AI/ML Infrastructure and Ops Engineer

AI/ML Infrastructure and Ops Engineer (AI/ML Training Platform).

As the Infrastructure and Ops Engineer, you will work on operations related our UAIS AI Studio (enterprise AI/ML platform), and in particular in relation to AI/ML training initiative supporting thousands of learners on the platform. This individual contributor (IC) role requires experience on working on large-scale AI/ML platforms guaranteeing stability, reliability, scalability, and performance. Experience with modern Infrastructure and DevOps tools and paradigms, as well as hands-on knowledge with major cloud-based services like Azure, AWS and Google Cloud Platform is a must.

Primary Responsibilities:

Continuous support: Provide continuous SRE support to thousands of geographically distributed learners on the UAIS platform: respond to tickets, triage support, liaise with customers.

Automation & DevOps: Improve existing Infrastructure as Code (IaC) according to best DevOps practices.

Systems Monitoring: Develop and maintain monitoring frameworks for UAIS infrastructure in relation to AI/ML training program

Security & Compliance: Collaborate with cybersecurity teams to ensure all systems and operations comply with industry standards and are secure against evolving threats.

Capacity Planning & Cost Optimization: Forecast and manage capacity requirements for the AI/ML training environment, while identifying opportunities to reduce costs without compromising performance.

Required Qualifications:

Bachelor s degree in computer science, information technology, or a related field.

5+ years of infrastructure experience: Proven experience working on large-scale, cloud-based, enterprise-level software platforms and deep understanding of multi-cloud architectures, specifically Azure, AWS, and Google Cloud Platform, with hands-on experience in cloud management.

3+ years of practical experience in Infrastructure-as-Code and CI/CD tools like Terraform, Git Actions and alike.

2+ years of practical experience in containerization technologies (Kubernetes, Docker) and orchestration

2+ years of practical experience in Scripting & Automation Skills: Advanced proficiency in scripting languages such as Python and Bash to support automation and system integration efforts.

Preferred Qualifications:

Security & Compliance Knowledge: Strong understanding of security best practices and experience ensuring compliance with relevant regulatory frameworks.

Machine Learning and LLM Operations: Exposure to modern tools and techniques in MLOps and LLMOps fields.

Exposure to AI/ML-specific infrastructure tools (e.g., MLflow, Kubeflow) for managing and deploying models at scale.

Exposure to a Regulated Industry: Experience working within a healthcare or regulated industry, with solid understanding of the unique challenges and compliance requirements.

Ability to work independently, manage multiple projects simultaneously, and adapt to changing priorities in a fast-paced environment.