Algorithm Engineer

Alpha X is an innovative high-tech manufacturing technology company pioneering the integration of advanced automation, transportation and AI-driven solutions to revolutionize traditional manufacturing processes. We harness the power of artificial intelligence, machine learning, and robotics to optimize production efficiency, enhance product quality, and foster sustainability across diverse high-tech industries.

**Responsibilities**:
1. Development of Intelligent Algorithms for Equipment and Processes: Develop algorithms for anomaly detection, fault diagnosis, remaining useful life prediction, endpoint detection, etc., using structured time-series data such as temperature, current, voltage, and flow rate.

2. Algorithm Engineering and Maintenance: Test, deploy, validate, debug, maintain, and iterate on developed algorithms/models to ensure stable, reliable, and functional performance.

3. Feature Engineering Algorithm Development: Develop and select usable features based on physical mechanisms, machine learning (including deep learning), or hybrid approaches that combine data-driven and mechanistic methods. Collaborate with other technical teams to develop fault prediction algorithms.

4. Field Research and Requirement Analysis: Conduct on-site investigations (travel required) to understand end-user needs and habits. Translate business requirements into technical requirements.

5. Feasibility Analysis and Data Preprocessing: Perform data organization, quality assessment, feasibility analysis, and preprocessing.

6. Pre-Sales Support and Technical Evaluation: Provide technical evaluations, guidance, and documentation during the pre-sales phase as needed.

7. Post-Sales Support and Consultation: Offer technical consultation and guidance based on customer needs during the post-sales phase.

8. Documentation and Knowledge Management: Prepare and manage code annotations, project documentation, and patents.

**Job requirements**:
1. Master’s degree or above in Mechanical Engineering, Automation, or related fields; Doctoral degree is preferred. Experience in algorithm development for semiconductor manufacturing projects is a plus.

2. At least 3 years of relevant experience in the development and engineering of fault prediction and diagnosis algorithms based on time-series data.

3. Proficiency in common statistical methods (e.g., time-series forecasting, linear regression, PCA, control charts) and machine learning techniques (e.g., reconstruction methods like AE, predictive methods like LSTM, classification algorithms like ANN, SVM, clustering methods like k-means, DBSCAN). Experience combining time-series feature engineering with machine learning algorithms for anomaly detection and diagnosis is required.

5. Proficiency in Python for implementing machine learning and time-series signal processing algorithms. Familiarity with open-source frameworks like PyTorch and TensorFlow is required.

6. Experience in parallel computing, data augmentation, data quality improvement, and GPU-based efficiency enhancement is a plus.

7. Strong learning and communication skills are preferred, including the ability to communicate business needs with non-technical users and translate them into technical requirements. Quick mastery of the fundamental principles of the modeling objects is advantageous.

8. User-centered mindset with an awareness of algorithm product design, considering functionality from the user's perspective and designing algorithms accordingly.

9. Good coding standards and documentation habits.

10. Excellent English reading and writing skills; fluency in speaking and listening is a plus.

11. Overseas academic background is preferred.
- Collaborative entrepreneurial spirit
- Winning through customers
- High ethical standards, openness and trust
- Expectations for results
- Respect and value people