AI / ML Engineer

• Support development of AI/ML models for test optimization, calibration improvement, and test-time reduction.
• Analyze optical test and manufacturing data to identify trends, correlations, anomalies, and improvement opportunities.
• Build and evaluate supervised ML models using Python libraries such as scikit-learn, XGBoost, or LightGBM.
• Assist in developing predictive models to estimate long-duration test outcomes from early-stage measurements.
• Support anomaly detection using statistical methods, Isolation Forests, autoencoders, or other ML-based approaches.
• Assist senior engineers in experiments involving Reinforcement Learning, Bayesian Optimization, or multi-armed bandit techniques.
• Develop Python scripts for data preprocessing, feature extraction, visualization, and reporting.
• Work with test engineers to understand optical test parameters such as ER, OMA, TDECQ, LUT calibration, bias currents, BER, and equalizer settings.
• Support integration of ML workflows with test automation frameworks, Python APIs, LabVIEW, or existing internal tools.
• Generate reports and dashboards to summarize model performance, test-time savings, yield impact, and data quality observations.
• Participate in debugging, validation, and documentation of AI/ML solutions before deployment.
• Collaborate with cross-functional teams including optical test, manufacturing, firmware, software, and data science teams.

Education & Experience

• Bachelor’s or master’s degree in Electrical Engineering, Electronics & Communication, Computer Science, Data Science, Applied Physics, or a related field.
• Fresh graduates or candidates with 0–2 years of experience may apply.
• Academic projects, internships, or coursework in AI/ML, data science, signal processing, optimization, or test automation are preferred.
• Exposure to hardware testing, manufacturing data, optical communication, or embedded/test systems is a plus.
• Prior experience with Python-based data analysis or ML model development is preferred.