About the role
AI summarisedAccenture is seeking a Machine Learning Engineer to design, build, deploy, and maintain ML models for intelligent digital products. The role involves collaborating with data scientists and engineers to create scalable ML solutions, with a focus on end-to-end pipelines, model monitoring, and production deployment.
BusinessFull-timeTechnology 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
- Experience with ML model monitoring tools and model drift detection
- Knowledge of data versioning tools (e.g., DVC, MLflow)
- Familiarity with microservices and container orchestration (e.g., Docker, Kubernetes)
- Exposure to real-world ML deployment challenges and optimizations