AIOps Advisory Researcher

***This is a hybrid role, and this candidate must be willing to work onsite three days a week in our Morrsiville, NC office.***

***This role requires fluent ability to speak Mandarin. Only candidates that are fluent in both English and Mandarin will be considered.***

Job Responsibilities:

• Design and implement cutting-edge AI models tailored for server failure diagnosis and anomaly detection.
• Leverage time-series analysis techniques to model and predict system behavior, identifying potential faults or irregularities based on historical data trends.
• Integrate machine learning algorithms to provide real-time predictions and root cause analysis.
• Refine data models to improve diagnostic accuracy and system reliability in mission-critical environments.
• Bridge communication and facilitate the collaboration between business groups on multiple critical business projects.
• Manage data, models, and infrastructure which is mandatory to align with BIS compliance.

Minimum Requirements:

• 5+ years of relevant work experience in coding and data management.
• Fluent in Chinese communication with professional proficiency in reading/writing technical documentation.
• Expertise in data management, data cleaning, feature engineering, and end-to-end ETL pipeline design.
• Advanced performance tuning experience with relational databases (MySQL/PostgreSQL) and NoSQL databases (MongoDB/Cassandra).
• Proficient in server hardware management, including hardware troubleshooting, cluster maintenance, and performance optimization for large-scale computing environments.

Preferred Requirements:

• Master's degree or higher in Computer Science, Software Engineering, or related fields.
• Experience in NLP, machine learning, deep learning, data mining, or pattern recognition.
• Strong familiarity with LSTM/CNN/RNN architectures.
• Experience with BERT, LLMs (Large Language Models), or related transformer-based models.
• Proficient in at least one machine learning framework (TensorFlow/PyTorch/Keras) with production-level implementation experience.
• Experience with Spark/Flink for building PB-scale data processing pipelines.
• Working knowledge of data lake technologies (Delta Lake/Hudi) and cloud data warehouses (Snowflake/Redshift).