Senior Manufacturing Data Analytics Engineer — AI & Automation

Allegro MicroSystems; Metro Manila; On-site; PHP 1,200,000 - 2,100,000; Full time

Job summary

Allegro MicroSystems in the Philippines is seeking a data/AI professional to accelerate its digital transformation in semiconductor manufacturing. You will design end-to-end, data-driven solutions, deploy AI systems into production, and lead cross-functional projects from inception to deployment while ensuring cybersecurity and data privacy compliance.

Join a team focused on innovation with purpose, delivering measurable improvements in production efficiency, reliability, and sustainable

Qualifications

• Bachelor’s or Master’s degree in a technical field such as data science, AI, CS or related engineering.
• 3–5 years of hands-on automation, data analytics and AI in semiconductor manufacturing.
• Experience deploying automated workflows and production AI systems.
• Experience integrating databases and cloud platforms into unified architectures.
• Knowledge of AI model lifecycle, data preparation, and dashboarding.

Responsibilities

• Design end-to-end data-driven solutions to improve production efficiency.
• Build predictive ML models and automated workflows.
• Create AI pipelines across databases, cloud platforms, and tools.
• Lead cross-functional projects and perform UAT with end users.
• Document solutions and provide training materials.

Skills

Data analytics

AI deployment

Automation

Cloud integration

Dashboarding

Education

Bachelor’s or Master’s in Data Science / AI / CS / EE/CE

Tools

Databases

Cloud platforms

ML lifecycle tools

Job description

Allegro MicroSystems in the Philippines is seeking a data/AI professional to accelerate its digital transformation in semiconductor manufacturing. You will design end-to-end, data-driven solutions, deploy AI systems into production, and lead cross-functional projects from inception to deployment while ensuring cybersecurity and data privacy compliance.

Join a team focused on innovation with purpose, delivering measurable improvements in production efficiency, reliability, and sustainable