Machine Learning Engineer I/II

Roles and Responsibilities: Technical Leadership Architect, design, and implement scalable machine learning systems for optimized content delivery, connectivity, and personalization. Lead decision-making for ML infrastructure, cloud-based data pipelines, and deployment strategies. Define best practices for ML system design, versioning, and continuous integration. ML Model Development Build, train, and deploy predictive and generative models using frameworks such as TensorFlow, PyTorch, and Scikit-learn. Optimize model performance for scalability, latency, and resource efficiency. Collaborate with data scientists and engineers to integrate models into production environments. Innovation & Research Explore emerging ML technologies and frameworks to enhance system performance. Evaluate new algorithms, architectures, and deployment techniques for business impact. Cross-functional Collaboration Work closely with product, data, and engineering teams to align ML initiatives with organizational goals. Provide technical mentorship and guidance to junior ML engineers. Monitoring & Optimization Establish robust monitoring, validation, and retraining workflows for deployed models. Ensure model explainability, reproducibility, and compliance with data governance standards.