3 дня назад
Senior Engineer, Automation Development Engineering (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Engineer, Automation Development Engineering (AI): Developing predictive models, scalable data pipelines, and automated analytics for precision manufacturing with an accent on process yield, defect prediction, and anomaly detection. Focus on building end-to-end machine learning workflows, translating complex models into operational recommendations, and presenting technical findings to engineering leadership.
Location: BangPa-in, Phra Nakhon Si Ayutthaya, Thailand; BangPa-In Building 2
Company
develops large-scale data storage systems and manufacturing infrastructure for AI-driven data environments, hyperscale data centers, cloud platforms, and enterprise infrastructure.
What you will do
- Develop predictive models and advanced statistical analyses for process yield and defect prediction.
- Build scalable data pipelines and analytics platforms for engineering use.
- Lead applied analytics projects in Phase 2 of the BEST Early Career Talent Program with mentor oversight.
- Partner with manufacturing and process engineers to embed data-driven methods into daily operations.
- Automate data collection, reporting, and anomaly detection.
- Prepare and present technical findings to engineering leadership, including cross-site reviews.
Requirements
- Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or Engineering with an advanced analytics or AI specialization, or equivalent experience.
- Fresh graduate or no more than 2 years of postgraduate experience.
- Advanced proficiency in Python, R, and/or SQL.
- Experience with machine learning, predictive modeling, or advanced statistical analysis.
- Research or thesis experience using data-driven methodologies.
- Strong analytical rigor, independent thinking, and the ability to translate complex models into operational recommendations.
Nice to have
- Thesis or published research in ML, AI, process analytics, or manufacturing intelligence.
- Experience with big data platforms, cloud analytics such as AWS, Azure, or GCP, or edge computing.
- Knowledge of time-series analysis, anomaly detection, sensor data analytics, manufacturing execution systems, or industrial IoT data.
- Experience building end-to-end ML pipelines from data ingestion through model deployment.
- Software engineering discipline, including version control and documentation.
Culture & Benefits
- Structured onboarding, mentorship, and professional development curriculum through the Early Career Talent program.
- Opportunities to contribute to projects affecting manufacturing yield, quality, and operational efficiency.
- Inclusive environment focused on diversity, belonging, respect, and contribution.
- Accessibility support is available throughout the application and hiring process.
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