SENIOR MLOPS ENGINEER WITH ML/AI

Role overview

Responsibilities

• check_circle Support application infrastructure to ensure the platform is optimized for performance and reliability.
• check_circle Build and maintain supporting infrastructure for cloud environments and applications.
• check_circle Lead the design and engineering of software systems for the AI/ML Platform, contributing to the full ML development life cycle.
• check_circle Identify and implement opportunities to automate and streamline ML development processes, fostering efficiency and effectiveness.
• check_circle Build and manage enterprise AI solutions using Azure AI Foundry & Azure's integrated platform (Azure OpenAI, AI Search, Prompt Flow),
• check_circle Use a wide range of Azure resources to implement scalable, reliable, and cost-efficient services.
• check_circle Work side by side with your engineers, guiding critical projects, using your subject matter expertise to solve complex problems.
• check_circle Perform and automate system administration services, including installation, configuration, maintenance, and disaster recovery
• check_circle Identify system-level issues related to OS configuration and virtual hardware bottlenecks.
• check_circle Provide automation, auditing, and other tooling for security, compliance, and resource usage. Monitor and improve processes for all deployments.
• check_circle Take ownership of operational excellence to establish and maintain business focused KPI's. Use these metrics not only as a basis for positive transformation, but also as a visible representation of your team's success.
• check_circle Maintain and take ownership of your tasks each sprint, ensuring time worked is logged, and details are added.
• check_circle US and EU projects based on advanced technologies.
• check_circle Competitive compensation based on skills and experience.
• check_circle Regular performance appraisals to support your growth.
• check_circle Flexibility in workspace, either remote or our welcoming office.
• check_circle Bonuses for article writing, public talks, and other activities.
• check_circle Generous time off, including vacation, national holidays, sick leaves, and family days.
• check_circle Personalized learning programs tailored to your interests and skill development.
• check_circle Free tech webinars and meetups organized by Svitla.
• check_circle Regular corporate online activities.
• check_circle Awesome team and a friendly, supportive community!

Basic qualifications

• Solid experience designing, implementing, and managing infrastructure for AI/ML or HPC workloads.
• Proven success in managing and optimizing CI/CD for an Azure-based SaaS application.
• Hands-on experience with standard DevOps tools, including Azure DevOps.
• Expertise in scripting with at least PowerShell or Bash.
• Understanding of configuration management tools like Terraform.
• Proven experience designing, implementing, and managing infrastructure for AI/ML or HPC workloads.
• Working knowledge of version control/source code management tools.
• Experience working in an agile software development life cycle.
• Knowledge of databases, including SQL and NoSQL
• Strong knowledge of web server configuration and management, such as IIS or Tomcat.
• Familiarity with local and wide area networking and associated technologies, e.g., switches, routers, firewalls, VPNs.
• Strong understanding of security principles.
• Bachelor’s Degree in Computer Science or a similar area of study.
• Experience working in a technical, fast-paced environment with high demand and high standards.
• Ability to assimilate information quickly under pressure.
• Excellent communication and collaboration skills.
• Ability to communicate effectively with multiple disciplines.
• Excellent analytical skills with the ability to drive reliability improvements.
• Strong planning skills to ensure business expectations are met, and projects are delivered on time.

Preferred qualifications

• Understanding of machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn, and their deployment in production environments.
• Familiarity with cloud-based networking (VNETs, NSGs, Route Tables, Hub/Spoke-based architecture, Private Endpoints, etc.).
• Strong understanding of CI/CD (YAML and Classic Pipelines).
• Experience with PaaS (Web Apps, Function Apps, Storage Accounts, Key Vaults, Azure Redis Cache, Azure Service Bus, API Management, Azure Data Factory, Azure Databricks).
• Experience in monitoring (New Relic, LogEntries, Rapid7, Azure Monitoring, etc).
• Some experience with containers/Docker, either for a microservice-based architecture or Service Oriented, etc.
• Familiarity with Git, ARM, Terraform, Ansible, Azure CLI, or similar.