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)
Lead AI/ML & MLOps Engineer executing projects from data foundations to model deployment. Collaborating with sales to drive AI/ML engagements for our clients.
Applied ML Engineer working on AI - driven insights at Kaseya. Collaborating with product teams to enhance features with machine learning and data analysis.
Adversarial Machine Learning Engineer conducting adversarial testing and simulations on LLM - driven AI systems for enterprise security. Collaborating with teams to validate and document findings.
MLOps Engineer managing infrastructure for large 2D and 3D media datasets at NBCUniversal. Responsible for automation, reproducibility, and performance of machine learning lifecycles.
Senior ML Engineer leading the strategic direction of machine learning infrastructure for global food delivery platform. Collaborating with Data Science team for seamless model deployment and innovation.
Machine Learning Intern/Co - op at Cohere working on developing and training models for AI applications. Join a team focused on advancing AI technology in an inclusive environment.
Machine Learning Engineer designing and deploying detection ML systems for social engineering defense platform at Doppel. Collaborating to mitigate evolving digital threats using AI.
Senior Software Developer responsible for designing and developing solutions in data engineering and machine learning. Collaborating with teams to deliver scalable software solutions with agile methodologies.
Senior ML Engineer responsible for designing and building ML pipelines for a Trust Scoring platform. Involves productionizing models and implementing MLOps best practices.
Principal Machine Learning Engineer designing the core ML systems for AI agents at Workday. Collaborating in cross - functional teams to integrate ML solutions into the platform.