Position Summary：

In the framework of “AI Trustworthiness” across industry sectors, this role will be engaged in the implementation of new methods and tools to assess the quality of products, processes and data involving AI. We work with regulators and standardization organizations to make sure artificial intelligence is safe, secure, and reliable.

Products and services that rely on artificial intelligence technology can currently not be tested with existing methods to assess safety, security, reliability, and conformance to legal and ethical requirements. Hence a new methodology is required to guide and continually assess the quality of AI throughout all stages of the life cycle. A crucial component of such methodology is the selection and quantification of quality metrics, as well as defining conditions of acceptability in relation to the scope of the AI product.

Job Responsibilities:

1. In close cooperation with and under the guidance of our Center of Excellence team, develop methodologies and throughout the entire product life cycle;

2. Develop and maintain technical specifications, testing protocols, and certification implementation rules for AI product testing and certification throughout the product life cycle;

3. Design specialized evaluation frameworks for AI verticals such as computer vision, NLP, and recommendation algorithms Design and execute functional testing, performance testing, robustness testing, and bias/fairness evaluation for AI products;

4. Perform adversarial sample testing, security vulnerability scanning, and ethical risk identification using testing tools;

5. Development of quality management systems to evaluate AI-based products, judge conformance to requirements, and provide conformity recommendations;

6. Service development and project implementation; 

7. Technical supporting of the digital activities of each BUs in COM GCN;

8. Cooperation with global groups and teams, eg. SMC, AVM, Digital Service.

Job Requirements:

1. Degree in Computer Science, Electronic/Electrical Engineering, or comparable with a focus on AI software engineering;

2. Bachelor's degree with 5+ years of experience, or Master's degree with 2+ years of experience;

3. Familiar with machine learning/deep learning principles, proficient in mainstream frameworks (PyTorch/ TensorFlow/Langchain), understanding of model training, evaluation, and deployment pipelines;

4. Fundamental knowledge on AI including machine learning, data analytics, deep learning to act as “AI Generalist”;

5. Knowledge of fundamental machine learning algorithms (e.g. Bayesian Networks, SVM, Random Forrest Networks, Deep Learning (RNN, CNN, LSTM, Transformer, GAN,), Knowledge Graph);

6. 2-3 years of work experience in industry or academia in commercial projects developing algorithm, script, software or firmware relevant to data analytics ,machine learning or AI agent/workflow;

7. Experience with a range of compiled and interpreted programming languages ,software engineering support tools (Experience with MLOps or AI content safety and hallucination detection is a big plus);

8. Team player with ability to work in international and multi-cultural teams;

9. Communications skills, fluent in English (oral and written) and Mandarin;

10. Ability to represent the company and discuss with external stakeholders.