Tata Electronics Private Limited (TEPL) is a greenfield venture of the Tata Group with expertise in manufacturing precision components.

Tata Electronics (a wholly owned subsidiary of Tata Sons Pvt. Ltd.) is building India’s first AI-enabled state-of-the-art Semiconductor Foundry. This facility will produce chips for applications such as power management IC, display drivers, microcontrollers (MCU) and high-performance computing logic, addressing the growing demand in markets such as automotive, computing and data storage, wireless communications and artificial intelligence.

Tata Electronics is a subsidiary of the Tata group. The Tata Group operates in more than 100 countries across six continents, with the mission 'To improve the quality of life of the communities we serve globally, through long term stakeholder value creation based on leadership with Trust.’

Responsibilities

• Research, design, and develop advanced machine learning and deep learning models to solve complex enterprise/manufacturing problems.
• Experiment with state-of-the-art algorithms (NLP, Computer Vision, Reinforcement Learning, etc.) to drive innovation.
• Collaborate with Data Engineers to curate high-quality datasets and optimize model performance.
• Conduct model evaluations, performance tuning, and error analysis.
• Present findings to stakeholders, providing data-driven insights and recommendations

Essential Attributes

• Out of the box thinking to deal with complex semiconductor & Electronics manufacturing problem
• Problem solving
• Highly motivated, critical thinking, open communication and team player
• Can work independently for daily trouble shooting
• Drive for Innovation

Qualifications

• Master’s or PhD (preferred) in Computer Science, Electrical/Electronic Engineering, or related discipline. A Bachelor’s degree with strong research/project experience may also be considered.
• 5 to 10 years of experience, In-depth industry or research experience in developing AI models. A track record of successful AI/ML projects deployed in production environments.
• Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of mathematical foundations (linear algebra, calculus, probability).
• Experience with data visualization and model explainability tools.

Experience Level

• Innovative mindset, ability to translate business problems into AI solutions, and strong communication for sharing complex research clearly.
• Publications in AI/ML conferences or journals.
• Experience with optimization algorithms and large-scale model training (GPU clusters, distributed computing).
• Domain knowledge in manufacturing or industrial processes.