1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, and maintain scalable machine learning pipelines for model training.
- Deploy and serve machine learning models as secure, production-ready services using Docker and FastAPI.
- Manage batch and real-time inference for marketing applications.
- Automate testing, model validation, and deployment workflows for ML projects.
- Orchestrate model versioning, packaging, registration, and end-to-end lifecycle management using MLflow or similar tools.
- Use Airflow and MLflow to support reproducibility and governance from experimentation through production.
- Monitor model performance, data drift, and system health, including alerts, dashboards, retraining, and tuning.
- Serve as a subject matter expert, collaborate across teams, make team decisions, provide solutions, mentor junior professionals, and improve workflows.
Requirements
- At least 5 years of experience in Machine Learning Operations; the posting also states a minimum of 3 years of experience.
- Strong engineering experience and advanced Python skills.
- Proficiency in Machine Learning Operations and a thorough understanding of infrastructure requirements for MLOps.
- Mandatory experience with MLflow and Airflow.
- Experience with cloud-based AI services, multi-cloud environments, machine learning frameworks, and production model optimization.
- Fifteen years of full-time education is required.
Benefits
- The position is based at the employer's Bengaluru office.
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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.