Senior Software Engineer - MLOps

Job Description :About the Role :

We are seeking a highly skilled Senior Software Engineer - MLOps (Python) to design, build, enhance, and stabilize a production-grade enterprise AI/ML platform that supports model training, validation, deployment, orchestration, and lifecycle management at scale.

This role is ideal for a software engineer who views MLOps as a disciplined software engineering practice rather than a collection of scripts or notebooks. The successful candidate will contribute to a class-based, API-driven, CI/CD-enforced MLOps ecosystem, focusing on reusable libraries, ML workflows, secure endpoints, schema-driven interfaces, automated testing, and cloud-native deployment strategies.

You will play a key role in modernizing platform capabilities, supporting the transition from Azure Pipelines to GitHub Actions, and improving platform scalability, maintainability, and engineering excellence.

Key Responsibilities :1. Core Engineering & MLOps Development :

• Design, develop, and maintain production-grade Python services using object-oriented programming principles and software design best practices.

• Build reusable, scalable, and maintainable components aligned with SOLID principles and separation of concerns.

• Extend and enhance enterprise MLOps frameworks supporting :

i. Model training

ii. Model validation

iii. Model registration

iv. Azure ML execution environments

v. Parameterized workflow orchestration

vi. CI/CD-driven deployment pipelines

• Develop and maintain high-performance ML inference services and APIs.

• Implement robust validation, exception handling, and fault-tolerant processing mechanisms.

• Build clean, schema-driven request/response interfaces using JSON schemas and validation frameworks.

• Create and maintain versioned APIs with backward compatibility considerations.

• Contribute to platform modernization initiatives, including migration from Azure Pipelines to GitHub Actions.

2. API & Service Engineering :

• Design and implement RESTful APIs for enterprise AI/ML applications.

• Develop OpenAPI/Swagger-compliant API documentation.

• Optimize endpoint performance, scalability, and reliability.

• Implement asynchronous processing using Python async/await patterns.

• Build concurrent processing solutions for I/O-intensive workloads.

3. CI/CD & Platform Automation :