Staff Engineer, Machine Learning

You will be one of the engineers on a focused AI team solving hard scientific problems in precision product development. You will own two real responsibilities from day one — not toy tasks, but actual team workflow contributions that senior engineers depend on. You will be introduced to physics-informed AI, Bayesian methods, and product development ML systems within your first year under direct mentorship from engineers and researchers who have worked at world-class institutions.

If you are the kind of person who learns fast and wants to be in the middle of hard problems early in your career, this is an unusual opportunity. Key

Experiment Tracking & Evaluation Reporting: Own M

Lflow experiment logging for assigned team model runs; conduct model evaluations using standard metrics; produce structured evaluation reports reviewed by team. Your reports directly inform model iteration decisions. Training Data Quality Validation: Validate training datasets jointly with team — feature distribution checks, label verification, anomaly flagging.

Your quality flags are the final check before data enters the model training pipeline. You close the data quality loop between workstreams. Deep Learning Model Contribution: Build and train CNN-based models for image classification and defect detection under team’s guidance.

Contribute to model evaluation cycles, configuration comparisons, and training run analysis. ML Pipeline Contribution: Package models in Docker; contribute t