Job Title : ML Ops Engineer

Experience : 6- 8 years of relevant experience

Location : Pune / Gurgaon / Noida / Bangalore

Role Overview :

The ML Ops Engineer will be responsible for building, deploying, and maintaining scalable machine learning pipelines and production-grade ML systems.

The role requires strong programming skills, hands-on experience with ML frameworks, and a solid understanding of software engineering and system architecture.

Key Responsibilities :

- Design, build, and maintain end-to-end ML pipelines from model development to production

- Deploy machine learning models as scalable and secure services

- Develop and manage REST APIs for ML modules and model inference

- Collaborate with data scientists and engineers to operationalize ML models

- Ensure reliability, performance, and scalability of ML systems in production

- Implement monitoring, logging, and versioning for models and data pipelines

- Optimize model performance, latency, and resource utilization

- Automate model training, testing, deployment, and rollback processes

- Ensure best practices for code quality, security, and maintainability

- Troubleshoot and resolve production issues related to ML workflows

- Contribute to system and software architecture design for ML platforms

- Maintain documentation for ML pipelines, APIs, and deployment processes

Required Skills & Competencies :

- Strong proficiency in Python for ML and backend development

- Strong working knowledge of SQL for data querying and analysis

- Hands-on experience with machine learning frameworks and libraries

- Solid understanding of data structures, algorithms, and modeling concepts

- Experience building and deploying ML modules in production environments

- Strong understanding of software engineering principles and system architecture

- Experience developing and consuming REST APIs

- Familiarity with CI/CD practices for ML workflows

- Strong debugging, problem-solving, and analytical skills

- Ability to work collaboratively across data science, engineering, and product teams

Educational Qualifications

- B.Tech / M.Tech / ME / MCA or equivalent qualification

Preferred Skills :

- Experience with cloud platforms for ML deployment

- Exposure to containerization and orchestration tools

- Experience with monitoring and observability tools for ML systems