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.