Senior Machine Learning Engineer

Job Requisition ID #

25WD92507

Position Overview

We are transforming how utilities manage one of the world's most precious resources: water.

Our AI-driven platform empowers water utilities to make smarter, real-time decisions for critical processes like demand forecasting and sewer overflows. By leveraging advanced machine learning and automation, we help utilities reduce costs, improve reliability, and minimize risks to public safety.

We're also reimagining how the operational workforce of the 21st century interacts with critical infrastructure - building intelligent systems that shape the future.

We're looking for impact-driven innovators passionate about applying machine learning and software engineering to solve real-world challenges.

As a Machine Learning Engineer, you will integrate and optimize AI solutions that enhance operational decision-making for billions of dollars in water infrastructure. You'll work on mission-critical systems using cutting-edge cloud technologies and ML frameworks 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

• 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)
• Excellent communication and collaboration skills

• Experience with time-series forecasting, optimization algorithms, or reinforcement learning
• Familiarity with distributed systems and containerization (Docker)
• Knowledge of Model Context Protocol (MCP) for integrating AI systems
• Practical experience with multi-tenant SaaS applications