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Strong Tier-1 brand but specialized ML/AI focus yields moderate applicant competition.
Deep ML/AI and automotive domain skills required, limiting easy transfer across industries.
Requires specialized ML/AI and automotive deployment expertise, creating strict screening filters.
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Own end-to-end development of advanced AI/ML models combining computer vision and time-series data for deployment in the automotive domain.
Design, implement, and validate models including CNNs, Transformers, LSTMs, GRUs, ARIMA, and Prophet for object detection, image segmentation, forecasting, and anomaly detection.
Perform data analysis, feature engineering, model optimization, and rigorous evaluation to ensure robust, computationally efficient predictive models.
Degree Required: B-Tech (Bachelor of Technology).
Experience Required: Not explicitly mentioned in the JD.
Technical Skills: Hands-on experience with deep learning architectures (CNNs, Transformers, LSTMs, GRUs) and traditional time-series methods (ARIMA, Prophet).
Domain Experience: AI/ML applied to both computer vision and time-series data, preferably for automotive applications not explicitly mentioned but implied.
Strong expertise in multi-modal AI/ML model development combining visual and temporal data sources.
Capable of independent end-to-end model lifecycle ownership including data analysis, feature engineering, and hyperparameter tuning.
Experienced in deploying computationally efficient and robust models validated with appropriate metrics in complex, real-world datasets.