AI Leader

Tata Electronics Private Limited

Tata Electronics

Tata Electronics

Job Summary:

We are seeking an experienced and forward-thinking AI Lead to architect and scale AI/ML initiatives across our semiconductor assembly and test operations. This role is pivotal to our smart manufacturing vision—leveraging data, automation, and AI to drive yield improvement, predictive quality, and operational excellence.

Key Responsibilities:

AI Strategy & Execution

• Define and execute the AI/ML roadmap aligned with business and manufacturing priorities. Champion data-driven decision-making across operations.

Use Case Leadership

• Identify and own high-impact AI use cases in areas such as:
• Defect classification & root cause analysis
• Predictive maintenance of equipment
• Process parameter optimization
• Yield and test performance forecasting

Model Development & Deployment

• Lead the design, training, and deployment of machine learning models using production and equipment data. Ensure real-time and scalable inference in factory environments.

Data Ecosystem Enablement

• Collaborate with IT and process engineering to build and optimize the data infrastructure—streamlining access to structured/unstructured data from test equipment, sensors, MES and material handling system.

Cross-Functional Collaboration

• Work closely with manufacturing, quality, test engineering, and IT teams to integrate AI into existing workflows and drive adoption across the plant floor.

Technology & Platform Ownership

• Select and manage AI platforms and MLOps pipelines that meet the reliability and traceability needs of high-volume semiconductor manufacturing.

Team & Capability Building

• Lead a team of ML engineers and data scientists. Hire, mentor, and develop talent while building an AI-first culture across the organization.

Qualifications:

Education:

Experience:

• 8+ years in AI/ML, including 3+ years in a leadership role
• Strong preference for experience in semiconductor, electronics, or discrete manufacturing environments

Technical Proficiency:

• Expertise in ML frameworks and languages (Python, SQL)
• Experience with edge computing, MLOps, and real-time data processing
• Familiarity with SECS/GEM, OPC-UA, and other fab equipment interfaces

Business & Domain Knowledge:

• Experience driving ROI from AI in manufacturing

Preferred:

• Experience with SPC, Six Sigma, or industrial statistics
• Exposure to digital twin technology or simulation modeling
• Background in industrial automation, smart factory platforms, or IIoT solutions
• Good understanding of OSAT workflows: wafer sort, die attach, wire bond, mold, trim & form, final test