Senior Engineer - AI/ML at Coherent in Hyderabad

Job description

Primary Duties & Responsibilities Design, develop, validate, and deploy machine-learning solutions that improve optical transceiver calibration quality, test time, yield, and equipment utilization. Build supervised-learning models for prediction, classification, regression, anomaly detection, and early test-outcome prediction using high-volume production and engineering test data. Evaluate and apply optimization techniques—including Bayesian optimization, reinforcement learning, and hybrid/model-based approaches—where they provide measurable benefit for multi-parameter tuning and expensive test operations. Develop robust feature-engineering, data-quality, model-training, and model-evaluation pipelines for test and trace data. Integrate ML inference and optimization services with production test software, Python APIs, databases, and existing automation frameworks. Establish model validation criteria, including accuracy, repeatability, test-time reduction, false-pass/false-fail risk, yield impact, and fallback behavior. Monitor production model performance, data drift, and operational failures; implement versioning, logging, alerting, rollback, and retraining mechanisms. Analyze test and manufacturing data to identify bottlenecks, correlations, failure signatures, and opportunities for test-suite optimization. Work closely with test-development, product engineering, manufacturing, and software teams to translate technical requirements into deployable solutions. Mentor junior engineers through technical reviews, design guidance, and hands-on problem solving. Prepare clear technical documentation, results summaries, and business-impact reporting for engineering and management stakeholders. Contribute to invention disclosures, patents, or technical publications where applicable. Education & Experience Bachelor’s or master’s degree in Computer Science, Electrical/Electronics Engineering, Applied Physics, Data Science, or a related discipline. 3–5 years of hands-on experience developing and deploying applied AI/ML solutions in an engineering, manufacturing, test, semiconductor, optics, industrial, or similar environment. Demonstrated experience delivering at least one ML solution beyond proof of concept, including integration, validation, and operational support. Experience working with time-series, sensor, measurement, manufacturing, test, or high-dimensional engineering data is strongly preferred. Experience in optical transceivers, semiconductor test, high-speed electronics, signal integrity, or hardware test automation is a strong advantage. Required Technical Skills Strong Python software-development skills, including clean, maintainable, testable, and production-oriented code. Hands-on experience with PyTorch, scikit-learn, XGBoost/LightGBM, or equivalent ML frameworks. Strong understanding of model development and evaluation: data preparation, feature engineering, cross-validation, metrics, bias/variance, model explainability, and error analysis. Experience with regression, classification, anomaly detection, and statistical analysis of engineering or manufacturing data. Experience building or consuming REST APIs and integrating ML components into larger software systems. Working knowledge of SQL and data-processing tools such as pandas, NumPy, and Parquet/CSV-based data pipelines. Familiarity with source control, code review, CI/CD, containerization, and Linux-based development environments. Strong problem-solving, communication, and cross-functional collaboration skills. Preferred Skills Experience with Bayesian optimization, reinforcement learning, multi-armed bandits, or constrained optimization applied to real-world systems. Experience with MLOps practices such as experiment tracking, model registry, model versioning, monitoring, drift detection, and retraining workflows. Experience with FastAPI, Docker, PostgreSQL, Elasticsearch, Airflow, MLflow, or similar production data and ML platforms. Familiarity with test automatio