Machine Learning Engineer (MLE) ll

AI & ML Development

• Build and deploy ML models using GenAI and Predictive AI for forecasting, optimization, and intelligent automation

• Apply NLP and document analysis techniques to extract actionable insights from design documents

Solution Architecture

• Design robust ML pipelines and architectures for enterprise-scale applications

• Ensure solutions align with organizational goals and technology standards

Data Engineering & Modeling

• Develop efficient data models and wrangling strategies for large, complex datasets

• Drive data discovery initiatives and communicate patterns and hypotheses to stakeholders

Software Engineering

• Implement ML frameworks and coding best practices using Python, TensorFlow/PyTorch

• Integrate solutions with Big Data technologies (Spark, Kafka, Hadoop) for real-time and batch processing

Visualization & Insights

• Create dashboards and visualizations to present ML-driven insights in a business-friendly format

• Translate model outputs into actionable recommendations for decision-makers

Testing & Quality

• Develop repeatable test strategies for ML models ensuring accuracy and reliability

• Certify releases for performance and customer experience

Collaboration & Stakeholder Engagement

• Work closely with product managers, data engineers, and business teams to identify high-value AI use cases

• Communicate technical concepts clearly to non-technical stakeholders