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Tier-1 brand plus metro location but senior, niche embedded ML focus reduces applicant density.
Role requires embedded automotive ML and sensor-fusion expertise, limiting cross-industry transferability.
Explicit 8–10 years plus specialized ML, embedded and domain skills imply strict filters.
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Design, build, and deploy scalable machine learning models and data pipelines for AI solution development in embedded automotive hardware.
Implement enterprise AI solutions and adapt to various solution hosting platforms like MiDAS, Modanna, Codemate.
Curate and maintain engineering datasets to ensure data accessibility, quality, security, and AI-readiness supporting multiple AI use cases.
Bachelor of Engineering (B.E.) degree.
8-10 years of relevant work experience.
Proficiency in Python, Java, C, SQL and experience with AI/ML frameworks and tools such as Flask, Streamlit, Pandas, NumPy, scikit-learn, Hugging Face.
Experience with data engineering tools, databases (MySQL, MongoDB), Docker, Apache Kafka, REST APIs, and AI solution hosting platforms.
Experienced in end-to-end AI/ML solution design and deployment specifically in embedded automotive or related industry environments.
Strong data engineering background with hands-on expertise in curating and managing high-quality, secure datasets for AI applications.
Familiar with scalable AI model development integrating computer vision, sensor fusion, and predictive maintenance use cases on embedded hardware.