ML Ops engineer

We are seeking a talented ML Ops engineer to join our team and play a key role in deploying, managing
and optimizing machine learning models in production. The ideal candidate will have a strong background
in both machine learning and software engineering, with experience in DevOps practices and cloud
computing.
Roles Responsibilities:
Collaborate with data scientists and software engineers to deploy machine learning models into
production environments.
Design and implement scalable and reliable ML pipelines for model training, evaluation and
deployment.
Develop and maintain infrastructure automation scripts for provisioning, configuration, and
orchestration using platforms such as Resource Manager (ARM) templates, Automation,
PowerShell, or other relevant tools.
Optimize ML pipelines for efficiency, scalability and cost-effectiveness
Monitor, optimize, and troubleshoot Azure/AWS resources and services to ensure high
availability, reliability, and performance of cloud-based applications and systems.
Implement security policies, access controls, and encryption protocols to safeguard Azure/AWS
environments and data, adhering to compliance and governance requirements.
Collaborate with development teams to streamline the continuous integration and continuous
deployment (CI/CD) process in Azure/AWS DevOps or similar tools for efficient application
delivery.
Provide expertise and support in areas such as Azure/AWS cost management, capacity planning,
scalability, and disaster recovery strategies.
Participate in the evaluation of new Azure/AWS offerings, technologies, and services to drive
innovation and improve the overall cloud environment.
Qualifications External/Internal
What you will need to succeed in the role: (Minimum Qualification and Skills Required)
Bachelors degree in Computer Science, Information Technology, or a related field; relevant
certifications such as Microsoft Certified: Azure Administrator Associate or Microsoft Certified:
Azure Solutions Architect Expert preferred.
INTERNAL
Strong proficiency in Python programming and familiarity with machine learning frame works
such as TensorFlow or Pytorch.
Proficiency in implementing and managing security, identity, and access management solutions,
leveraging Active Directory, Security Center, and other