AI/ML Engineer

Artificial Intelligence Engineer

About TI
As a global semiconductor company, we design, manufacture, test and sell analog and embedded processing chips to nearly 100,000 customers. Our products enable electronics everywhere and in things you experience every day - from health care, smart homes and connected cars to drones, smart phones and more. Our passion to create a better and more sustainable world by making electronics more affordable through semiconductors drives us to make our technology smaller, more efficient, more reliable and more affordable.

About the Job
The AI Engineer will drive implementation of artificial intelligence and machine learning solutions to enhance semiconductor back-end manufacturing operations. The role will involve close collaboration with manufacturing teams, data scientists, product and process engineers to identify opportunities and implement AI-driven solutions that improve operational efficiency, quality, and yield.

This position requires a strong understanding of AI/ML technologies, experience with semiconductor manufacturing, and a passion for applying data-driven techniques to solve complex industrial problems.

Responsibilities include:

• Collaborate with cross-functional teams and domain experts to identify opportunities for AI integration in workflows.

• Analyze and preprocess large datasets from manufacturing equipment, sensors, and logs to enable effective machine learning applications.

• Lead proof-of-concept projects and pilot programs to demonstrate the value of AI applications in manufacturing settings.

• Develop and deploy AI/ML models for defect detection, yield improvement, process optimization, and predictive maintenance in semiconductor back-end manufacturing processes.

• Provide technical documentation, training, and support to ensure seamless adoption of AI solutions by production teams.

• Monitor AI systems performance and implement enhancement.

• Stay updated with the latest advancements in AI/ML and propose innovative solutions applicable to semiconductor manufacturing.

• Set up and manage AI development and production infrastructure.

• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.

• Build data ingest and data transformation infrastructure.

• Identify transfer learning opportunities and new training datasets.

• Build AI models from scratch and help product managers and stakeholders understand results.

• Deploy AI models into production.

• Create APIs and help business customers put results of your AI models into operations.

• Keep current of latest AI research relevant to our business domain.

• Collaborate with Data Analytics team to integrate and implement large scale data solutions. 

• Participate in fast-paced prototyping to identify improvement opportunities in manufacturing systems.