The Machine Learning Engineer exercises good judgment and is responsible for working independently with minimal instruction to prioritize work and resolve moderately complex issues. This role builds, optimizes, and scales machine learning models while contributing to innovative AI-driven solutions, and assisting users in understanding ML predictions. Collaboration with cross-functional teams ensures successful project outcomes.

Model Development and Training: Ability to manipulate (i.e. optimize) model training and model serving frameworks.

Feature Engineering: Engineer features from raw data, including unstructured formats, to enhance model effectiveness.

Algorithm Selection: Experiment with algorithms to select the most effective ones for project objectives.

Model Evaluation: Use advanced metrics to validate model performance and improve reliability.

Model Inference: Algorithmic and System level optimizations for inference. Building reliable production model serving platform supporting a variety of accelerators.

Mentorship: Lead technical design discussions and training to other engineers

Troubleshoot complex production issues involving ML