Job Opening For Azure DevOps SRE/ Machine Learning ;0-6yrs Experienced /Any computer science or software Degree or engineering graduates or relevant field Year of Passing graduates: 2015 – 2024( Job Code RT 1185)

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Interested candidates kindly apply before 27/06/2024.

CV must be in PDF format, saved with your Full name.

Hiring for Developer/programmer !!!

Location: Bangalore, Karnataka

Technology: Machine Learning Azure DevOps SRE
Employment Type: Full Time/Permanent
Role: Developer/programmer
Experience: 0 – 6 years
Eligibility: Any computer science or software Degree or engineering graduates or relevant field
Year of Passing graduates: 2015 – 2024
Salary: Min INR 6,00,00 – Max INR 24 LPA
Job description
➢ The software engineer will be responsible for understanding the requirements and designing the optimum solution using AI applications.
Responsibilities:
➢ As Data Scientist/ML Engineer:
• Develop ML models and experiment with different algorithms;
• Conduct feature engineering and model selection;
• Train, test, and validate models;
• Evaluate model performance and iterate for improvement;
• Collaborate with data engineers to integrate data pipelines.
➢ As DevOps Engineer/ML Ops Engineer:
• Design and implement Continuous Integration/Continuous Deployment (CI/CD) pipelines for ML
models;
• Automate the deployment of ML models to different environments (e.g., Staging, Production);
• Monitor model performance post-deployment to ensure stability;
• Work on containerization (e.g., Docker) and orchestration (e.g., Kubernetes);
• Implement version control and rollback mechanisms for models.
➢ As Software Engineer/Back-end Engineer:
• Integrate ML models with existing applications or services;
• Ensure APIs are well-designed for model deployment;
• Work on the scalability and reliability of back-end systems;
• Handle communication between different components of the system.

Requirements:
➢ Azure Machine Learning DevOps Engineer Skill & Experience:
• Knowledge of Machine learning and Data Science;
• Understanding of ML models Knowledge of common ML algorithms, model training and
evaluation;
• Feature Engineering Ability to work with data to create features for ML models;
• Model Validation Understanding of techniques to validate and test ML models.
➢ DevOps & CI/CD Skill & Experience:
• CI/CD Pipeline Design Designing CI/CD pipelines for ML models using tools including Azure
DevOps or GitHub Actions;
• Automation Automating ML workflows including data ingestion, model training, and
deployment.
• Infrastructure as Code (IaC) Knowledge of IaC tools including Terraform or Azure Resource
Manager (ARM) templates to deploy infrastructure.
➢ Cloud Infrastructure & Services Skill & Experience:
• Azure Services In-depth knowledge of Azure Services including Azure Machine Learning, Azure
Kubernetes Service, Azure Functions, Azure Data Factory, and Azure Databricks;
• Containerization & Orchestration Proficiency using Docker for containerization and Kubernetes
for orchestration;
• Monitoring & Logging Knowledge of Azure Monitor, Azure Application Insights, and Azure Log
Analytics to monitor and troubleshoot ML deployments.
➢ Software Engineering & Programming Skill & Experience:
• Programming Languages Strong proficiency in Python, Spark/SQL (prefer knowledge of R, Java,
or C#, as well as);
• APIs & Back-end Services Ability to build and interact with RESTful APIs, as well as familiarity
with frameworks including Flask, Django, or FastAPI;
• Version Control Experience with Git and Git-based workflows.
➢ Security & Compliance Skill & Experience:
• Identity & Access Management Knowledge of Azure Active Directory for managing permissions
and roles;
• Data Security Understanding of data encryption, secure storage (e.g., Azure Key Vault) and
compliance with regulations (e.g., GDPR, HIPAA);
• Threat detection Familiarity with security practices and tools including Azure Security Center.
➢ Collaboration & Communication Skill & Experience.
• Cross-Functional collaboration Ability to work with data scientists, software engineers, and
product managers;
• Agile & Scrum Understanding of Agile methodologies and experience working in Agile
environments;
• Communication Ability to communicate complex technical concepts to non-technical
stakeholders.
Bonus Points:

➢ Proven experience in integrating AI/ML frameworks and libraries into enterprise applications.
➢ Demonstrated success in mentoring and developing junior engineers.
Benefits:
➢ Competitive salary and benefits package commensurate with experience.
➢ Opportunity to lead a high-impact project with significant growth potential and industry recognition.
➢ Work in a collaborative and supportive environment with global colleagues at the forefront of
innovation.
➢ Continuous learning and development opportunities.
➢ Good written and verbal communication skills

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