AI/ML Engineer - Remote / Telecommute

Requirements

• 5+ years of hands-on experience in applied machine learning, with a focus on regression, forecasting, or optimization.
• Proven experience in production-grade ML pipelines, from experimentation to deployment.
• Strong grasp of data science concepts such as cross-validation, quantile modeling, and model safeguard techniques.
• Strong background in Python and data science libraries, with the ability to write clean, efficient, and production-ready code.
• Experience on Git and related workflows, code review processes, automated testing, and CI/CD pipelines.
• Solid understanding of data lifecycle management, including time-series feature engineering and retraining strategies.
• Experience with ML model monitoring, versioning, and continuous retraining frameworks.
• Familiarity with cloud ML ecosystems (Azure or AWS).
• Experience with Azure ML, Cosmos DB, Service Bus, and Kubernetes.
• Experience with AWS Sage Maker, ECS Fargate, SQS/Event Bridge, and Document DB.

Responsibilities

• Design, train, and validate machine learning models that improve process performance and stability in concrete batching operations.
• Lead end-to-end model development, from data exploration and feature engineering to deployment and validation.
• Define and implement retraining and validation strategies that ensure continuous performance improvement.
• Propose data selection and quality control methods to improve training representativity.