IN
Full time
🤖 AI / ML
MLE/MLOps, OOPs Python, Databricks, Azure at Infosys
Listed by DevShelfHub
Bangalore, India
Hybrid
Senior · 5–8 yrs
About the Role
Machine learning engineering and MLOps are critical for productionizing AI at enterprise scale, and Infosys is hiring MLE/MLOps engineers in Bengaluru. Infosys is hiring for a role focused on OOPs Python, Databricks, and Azure to design, develop, and deploy scalable ML models with end-to-end MLOps lifecycle management.
This position sits within the Data & Analytics Unit and covers ML engineering, cloud platform integration, and big data pipeline optimization.
What you'll do
- Design, develop, and deploy scalable ML models and AI solutions
- Build end-to-end pipelines covering data ingestion, feature engineering, model training, evaluation, and deployment
- Apply advanced techniques for model optimization, validation, and explainability
- Design and implement MLOps frameworks for CI/CD/CT with MLflow for experiment tracking
- Automate model deployment, versioning, monitoring, and rollback strategies
- Implement model performance tracking, drift detection, and alerting systems
- Write scalable, modular OOPs Python with APIs and backend services for model serving
- Build and optimize pipelines using Azure Databricks, PySpark, and Delta Lake
- Manage Databricks clusters, jobs, and workflows; optimize Spark jobs for performance
- Design ML solutions using Azure services and integrate with Azure DevOps CI/CD
- Develop robust data pipelines and integrate ML models with downstream applications via APIs/microservices
What we're looking for
- 5-8 years work experience
- Bachelor of Engineering, BTech, BSc, BCA, MTech, MSc, or MCA
- Primary skills: Machine Learning, Python
- Experience with feature stores and model monitoring tools
Skills & Technologies
Required
5-8 years work experience
Bachelor of Engineering, BTech, BSc, BCA, MTech, MSc, or MCA
Primary skills: Machine Learning, Python
Experience with feature stores and model monitoring tools
Knowledge of Docker and Kubernetes (containerization)
Familiarity with streaming (Kafka, Event Hub)
Experience with Lakehouse architecture (Delta Lake)
Preferred Skills
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- This role offers end-to-end ML engineering ownership from model development through production MLOps on Azure and Databricks.
- Design, develop, and deploy scalable ML models and AI solutions
- Build end-to-end pipelines covering data ingestion, feature engineering, training, evaluation, and deployment
- Apply advanced techniques for model optimization, validation, and explainability
- Design and implement MLOps frameworks for CI/CD/CT (continuous training)
- Automate model deployment, versioning, monitoring, and rollback strategies
- Implement model performance tracking, drift detection, and alerting systems
- Write scalable, modular OOPs Python code with APIs and backend services
- Build and optimize pipelines using Azure Databricks and PySpark
- Design ML solutions using Azure ML, ADLS, Data Factory, Key Vault, and Synapse
- Integrate ML pipelines with Azure DevOps CI/CD pipelines
About Infosys
Infosys is a global leader in next-generation digital services and consulting, enabling clients in more than 50 countries to navigate their digital transformation. The Data & Analytics Unit delivers data-driven solutions across machine learning engineering, cloud platforms, and enterprise AI deployments.
- Industry
- Technology
- Company Size
- 500+
- Website
- infosys.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 5–8 years
- Location
- Bangalore, India
- Work Mode
- Hybrid
- Category
- AI / ML
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