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Strong Tier-1 brand, broad ML skillset required, and metro location increase applicant competition.
Core ML skills transferable, but automotive deployment and multimodal data raise domain specificity.
High technical specialization across CV and time-series, but no explicit years makes filters moderately strict.
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Develop and deploy advanced machine learning models utilizing both visual (computer vision) and time-series data targeting automotive applications.
Perform end-to-end model development including data analysis, feature engineering, training, evaluation, and optimization of deep learning and traditional ML models.
Implement state-of-the-art algorithms (e.g., CNNs, Transformers, LSTMs, ARIMA) and validate models to ensure accuracy and computational efficiency.
Technical expertise in advanced AI/ML model development including computer vision and time-series analysis.
Experience with deep learning architectures such as CNNs, Transformers, LSTMs, GRUs, and statistical time series models like ARIMA or Prophet.
Degree Requirement: B-Tech (Bachelor of Technology).
Work Experience Required: Not explicitly mentioned in the JD.
Strong track record in hands-on development and deployment of multi-modal AI/ML models combining image and sequential data.
Experience working in or targeting models for the automotive domain or similarly complex, high-stakes environments.
Ability to independently optimize and validate models balancing accuracy and computational performance.