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Societe Generale Global Solution Centre
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Lead Software Engineer -AIOps & Devops

Lead Software Engineer -AIOps & Devops

Societe Generale Global Solution Centre

2 - 7 years

15 - 20 Lacs

Bengaluru

Posted:4 days ago| Platform:

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Skills Required

kubernetes continuous integration cd python ms azure scikit-learn elk azure machine learning microsoft azure ci/cd machine learning azure devops docker ansible microsoft flow tensorflow spark kafka pytorch jenkins prometheus communication skills

Work Mode

Work from Office

Job Type

Full Time

Job Description

As a AI Ops Expert , Responsible and full ownership for the deliverables with greater defined quality standards with defined timeline and budget

Design, implement, and manage AIops solutions to automate and optimize AI/ML workflows.

Collaborate with data scientists, engineers, and other stakeholders to ensure seamless integration of AI/ML models into production.

Monitor and maintain the health and performance of AI/ML systems.

Develop and maintain CI/CD pipelines for AI/ML models.

Implement best practices for model versioning, testing, and deployment.

Troubleshoot and resolve issues related to AI/ML infrastructure and workflows.

Stay up-to-date with the latest AIops, MLOps, and Kubernetes tools and technologies.

Requirements and skills

Bachelors or Masters degree in Computer Science, Software Engineering, or a related field.

2-7 year of relevant experience

Proven experience in AIops, MLOps, or related fields.

Strong proficiency in Python and experience with FastAPI.

Strong handson expertise on Kubernetes (Or AKS)

Hands-on experience with MS Azure and its AI/ML services, including Azure ML Flow.

Proficiency in using DevContainer for development.

Knowledge of CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.

Experience with containerization and orchestration tools like Docker and Kubernetes.

Strong problem-solving skills and the ability to work in a fast-paced environment.

Excellent communication and collaboration skills.

Preferred Skills:

Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.

Familiarity with data engineering tools like Apache Kafka, Apache Spark, or similar.

Knowledge of monitoring and logging tools such as Prometheus, Grafana, or ELK stack.

Understanding of data versioning tools like DVC or MLflow.

Experience with infrastructure as code (IaC) tools like Terraform or Ansible.

Proficiency in Azure-specific tools and services, such as:

Azure Machine Learning (Azure ML)

Azure DevOps

Azure Kubernetes Service (AKS)

Azure Functions

Azure Logic Apps

Azure Data Factory

Azure Monitor and Application Insights

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Societe Generale Global Solution Centre

Banking

Paris

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Lead Software Engineer -AIOps & Devops