20 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, and maintain scalable ML training pipelines.
- Deploy and serve machine learning models as secure, production-ready services using Docker, FastAPI, and AWS.
- Manage batch and real-time inference workflows.
- Implement CI/CD pipelines, automated testing, model validation, and deployment workflows with GitHub Actions.
- Orchestrate the ML lifecycle, including model versioning, packaging, registration, and governance with MLflow and Airflow.
- Monitor model performance, data drift, alerts, dashboards, and production system health.
- Initiate model retraining or tuning to maintain accuracy and efficiency.
- Collaborate across multiple teams, contribute to decisions, solve team-level and cross-team problems, and facilitate knowledge sharing.
- Monitor project progress and alignment with strategic goals.
Requirements
- At least 5 years of experience in Machine Learning Operations.
- Proficiency in Machine Learning Operations.
- Strong understanding of cloud-based AI services and deployment strategies.
- Multi-cloud experience.
- Experience with machine learning frameworks.
- Mandatory experience with MLflow and Airflow.
- Ability to implement and optimize machine learning models for production environments.
- 15 years of full-time education.
Benefits
- The position is based at the Accenture office in Bengaluru.
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.