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Job Summary
To support our extraordinary teams who build great products and contribute to our growth, we’re looking to add a AI Engineer located in Shanghai Waigaoqiao site.
Reporting to Automation Engineering Director, the AI Engineer role will focus on reliability modeling, predictive analytics, and anomaly detection, applying machine learning and artificial intelligence techniques to drive data‑driven insights, improve system and product reliability, and enable proactive decision‑making across business and engineering functions.
What a typical day looks like:
- Collaborate closely with cross‑functional teams including product, engineering, quality, and manufacturing to understand business challenges and translate them into AI/ML solutions.
- Design, develop, and optimize machine learning models for reliability modeling, such as failure prediction, risk estimation and prescript the required actions.
- Build and refine predictive analytics models to support trend analysis, performance degradation forecasting, and early defect detection.
- Develop and deploy anomaly detection models to identify abnormal patterns, data drift, or system risks in both pre-run and real‑time scenarios.
- Own the end‑to‑end ML lifecycle, including data preparation, feature engineering, model training, validation, production deployment, and ongoing monitoring.
- Ensure models are robust, scalable, interpretable, and aligned with business objectives and operational constraints.
- Prepare technical documentation, analysis reports, and model performance summaries; participate in technical reviews and stakeholder presentations.
- Continuously improve model performance and solution effectiveness based on feedback, monitoring results, and evolving business needs.
The experience we’re looking to add to our team:
Experience:
- 4–6 years in AI/ML development, with projects in reliability modeling, predictive analytics, and anomaly detection.
- Proven track record of deploying ML models in production environments.
Education:
- Bachelor’s or Master’s in Computer Science, Data Science, Electrical/Computer Engineering, or related field.
- Advanced degree preferred.
Technical Skills:
- Good experience in Al algorithms of Classification & Detection, Time-Series & Predictive Models, Anomaly Detection, Reinforcement Learning, Clustering & Recommendation.
- Python, R, TensorFlow, PyTorch, Scikit‑Learn.
- Statistical modeling, time‑series forecasting, reliability engineering.
- Anomaly detection algorithms, predictive maintenance systems.
- Cloud ML platforms (AWS SageMaker, Azure ML, GCP AI).
- Strong coding practices (version control, CI/CD, unit testing).
Core Competencies:
- Strong problem‑solving and analytical mindset.
- Ability to work independently with minimal supervision, or collaboratively in teams.
- Strong programming and coding discipline across multiple languages.
- Excellent communication and presentation skills to technical and non‑technical audiences.
- Teamwork, adaptability, and proactive engagement.
- Professional documentation and reporting skills.
What you’ll receive for the great work you provide:
- Social insurance
- Life Insurance
- PTO
Job Category
Design, Process & Technology EngineeringRequired Skills:
Optional Skills:
Flex is an Equal Opportunity Employer and employment selection decisions are based on merit, qualifications, and abilities. We do not discriminate based on: age, race, religion, color, sex, national origin, marital status, sexual orientation, gender identity, veteran status, disability, pregnancy status, or any other status protected by law. We're happy to provide reasonable accommodations to those with a disability for assistance in the application process. Please email accessibility@flex.com and we'll discuss your specific situation and next steps (NOTE: this email does not accept or consider resumes or applications. This is only for disability assistance. To be considered for a position at Flex, you must complete the application process first).
