AI/ML Engineer
Tasks
- Analyze optical test and manufacturing data
- Automate test workflows and pipelines
- Build machine learning models for test optimization
- Collaborate with cross-functional engineering teams
- Debug validate and document machine learning solutions
- Develop predictive models for test outcomes
- Develop python scripts for preprocessing and reporting
- Generate model performance reports and dashboards
- Integrate machine learning workflows with test automation tools
- Perform anomaly detection
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Autoencoders | Bayesian optimization | Classification | Clustering | Data Preprocessing | Data Visualization | Feature Engineering | Feature extraction | Git | Isolation Forest | Jupyter Notebooks | Lab Equipment | LabVIEW | LightGBM | Machine Learning | Matplotlib | Model Evaluation | NumPy | Pandas | PyTorch | Python | Regression | Reinforcement Learning | SQL | Scikit-learn | Series analysis | Statistical Analysis | TensorFlow | Test automation | Time Series | Time Series Analysis | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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