Machine Learning Developer leveraging AI to enhance decision-making in water utilities infrastructural systems. Integrating and optimizing cutting-edge ML solutions in an agile environment.
Responsibilities
Implement, integrate, and optimize AI models for predictive analytics, operational decision-making, and anomaly detection within production systems
Build scalable, cloud-based ML pipelines and APIs using Python, FastAPI, and AWS services (e.g., SageMaker, Lambda)
Collaborate on the end-to-end ML lifecycle: data ingestion, feature engineering, model evaluation, and deployment
Work with large, complex datasets (including time-series and sensor data) to extract actionable insights
Ensure seamless integration of AI components into our SaaS platform with high reliability and performance
Design and implement agentic workflows that enable autonomous decision-making and orchestration of AI-driven tasks
Contribute to backend architecture, algorithm design, and software engineering best practices
Implement robust testing strategies (unit, integration, performance) and CI/CD pipelines for production-grade systems
Stay ahead of emerging ML technologies and contribute to open-source projects
Requirements
Bachelor’s degree or Master's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
3-5+ years of experience in machine learning and software development for production systems
Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
Experience with cloud-based ML services (AWS SageMaker preferred)
Solid understanding of data structures, algorithms, and software design principles
Familiarity with SQL/NoSQL databases and handling large-scale datasets
Experience building and deploying APIs and microservices
Knowledge of CI/CD pipelines and version control (Git)
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