What You’ll Do

• Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance.
• Configure and manage Azure cloud resources to support machine learning workloads efficiently.
• Collaborate with Azure administrators to ensure scalable and reliable infrastructure for MLOps.
• Implement Azure-based deployment pipelines for deploying machine learning models into production environments.
• Implement test automation script to monitor & validate the deployment process.
• Work alongside data engineers to develop and maintain data pipelines on Azure, ensuring proper data governance and integration with MLOps pipelines.
• Implement best practices for data versioning, lineage tracking, and other data management.
• Implement test automation script to monitor & validate the deployment process.
• Ensure that MLOps processes on Azure adhere to security and regulatory standards.
• Monitor and troubleshoot application and infrastructure issues and implement solutions in a timely manner.
• Collaborate with development and BI teams to ensure code quality and application performance.
• Stay updated on the latest Azure MLOps tools and services and integrate improvements into existing processes.

What You Know

• Should have a minimum of 8+ years of experience.
• Experience in implementing MLOps processes and solutions within the Azure ecosystem.
• Proficiency in Azure cloud services, including AzureML, Azure DevOps, Azure Kubernetes Service (AKS), Azure Databricks, and other relevant Azure services.
• Strong knowledge of machine learning frameworks and tools compatible with Azure and scikit-learn.
• Familiarity with Azure Resource Manager templates and Infrastructure as Code (IaC).
• Experience with version control systems, particularly Git, and CI/CD pipelines using Azure DevOps.
• Should have implemented test automation scripts to validate the deployment process.
• Scripting and coding skills, with proficiency in languages such as Python, PySpark, PowerShell, or Azure CLI.
• Understanding of security and compliance standards within the Azure ecosystem.
• Should have experience in executing Azure MLOps project
• Problem-solving and troubleshooting abilities.
• Should have cross-global location experience and be able to handle a team in an onshore-offshore model
• Having ML-related certifications can be a plus, such as Microsoft Certified: Azure AI Engineer Associate or Databricks ML Engineer

Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

Benefits

• In addition to competitive salaries and benefits packages, Nisum US offers its employees some unique and fun extras:
• Professional Development - We offer in-house technical training and professional learning programs aimed at developing skills across a broad spectrum of topics such as technology, leadership, role-based training, and process expertise. We also offer an annual stipend for employees to attend external courses in order to maintain professional certifications
• Health & Wellness Benefits - We believe that your health and welfare are important, and we strive to ensure that you have affordable options available to you, including some plans that are subsidized for employees and their families up to 90%. We also have dental and vision plans in the US where Nisum pays 100% of premiums for employees
• Volunteerism Pay - We believe in giving back and in the US, our employees are eligible for up to 40 hours of paid time off each year to volunteer towards the causes that they are most passionate about. This is in addition to personal PTO and paid holidays
• Additional Benefits - We offer all the other important benefits to keep employees and their families healthy and financially secure, such as 401(k) retirement savings with a company match, pre-tax parking and transit programs, disability insurance, and Basic Life/AD&D, alongside exclusive employee discounts on a wide variety of products and services

Compensation Band

• $135-140k per year