About the role
AI summarisedAs an ML Engineer at Accenture, you will design, build, deploy, and maintain machine learning models that power intelligent, data-driven digital products. You will collaborate with cross-functional teams to translate complex business needs into scalable ML solutions that deliver measurable impact for leading organizations.
ConsultingOnsiteTechnology Architecture
Key Responsibilities
- Design, develop, and operationalize machine learning models to support digital product features and analytics capabilities.
- Build and maintain end-to-end ML pipelines, including data preparation, model training, validation, and deployment.
- Develop and expose inference services via APIs for real-time and batch use cases.
- Implement model monitoring, performance evaluation, and lifecycle management practices.
- Optimize models and pipelines for scalability, reliability, and efficiency in production environments.
- Collaborate closely with cross-functional teams to translate business requirements into ML solutions.
- Maintain clear documentation across model design, processes, and deployment workflow.
Requirements
- Strong programming skills in Python for model development and data processing.
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience deploying models into production environments using APIs or containerized services.
- Familiarity with building data pipelines for feature engineering and model training.
- Understanding of MLOps practices, including CI/CD, monitoring, and automated workflows.
- Experience working with cloud platforms and distributed computing tools.
- Strong analytical and problem-solving skills with attention to detail.