CENTRE FOR ADVANCES IN RELIABILITY AND SAFETY LIMITED

Centre for Advances in Reliability and Safety Limited (CAiRS), initiated by The Hong Kong Polytechnic University, is established in 2020 with its operation located in the Hong Kong Science Park, New Territories, Hong Kong. The mission of CAiRS is to bridge academic and industrial counterparts to introduce and implement artificial intelligence methods and prognostic techniques to advance reliability and safety. The goal of the Centre is to improve reliability and safety of critical components and devices, products, systems and sub-systems designed, commissioned and/or manufactured by Hong Kong companies and enterprises. More information about the company can be found at http://www.cairs.hk.

Lead Engineer/ Senior Engineer (Ref. No.: CAiRS-LE/SE/P4.3) 

Duties

The appointees will report to Programme Manager and assist in planning and monitoring research projects – “Functional safety verification of systems that implement AI”. They will be required to:

  1. work with industry counterparts in consolidating academic research into tangible deliverables;
  2. steer the project, and ensure good and appropriate applicability to commercial/industrial partners;
  3. coordinate the delivery, installation and testing of the equipment; and ensure the equipment being properly installed, tested and commissioned at the Centre;
  4. manage research and development activities including technical and financial aspects, and other project administrative tasks such as preparing project updates and reports;
  5. work closely with research colleagues of the teams;
  6. coordinate with local and overseas universities, research institutions and business partners, and handle enquiries in a professional manner; and
  7. perform any other duties as assigned by the Centre Director or his delegates.

Qualifications

Applicants should:

  1. have a doctoral degree in Industrial Engineering, Electrical Engineering, Mechanical Engineering or a relevant discipline;
  2. have at least five years of research/relevant work experience with knowledge of corporate product development;
  3. have work experience in leading data science projects and conducting reliability management;
  4. have work experience in building and deploying large scale machine learning models, e.g. randomforest, xgboost, lightgbm, LSTM, Bert, etc;
  5. be well-organized, capable to work under pressure and able to handle multi-tasking assignments in a multidisciplinary team;
  6. have excellent interpersonal skills; and
  7. have a good command of written and spoken English and Chinese, with proficiency in Putonghua being an advantage.

Preferences will be given to those with work experience in any big data & cloud solution, e.g. HIVE, spark, Hadoop, Azure or AWS, etc.

Remuneration 

A highly competitive remuneration package will be offered. Applicants should state their current and expected salary in the application.

September 2021

Deadline for application: Recruitment will continue until the position is filled.

Application Guidelines

  1. Please return the completed application form, together with a detailed curriculum vitae, to the CAiRS by email to careers@cairs.hk 
  2. Application form can be downloaded from here.
  3. The CAiRS reserves the right to fill or not to fill the position. The personal data in relation to your application will be used by CAiRS to assess your suitability for assuming the position you are applying for, and to determine the remuneration and benefits package, if applicable.
  4. Please read the “Personal Information Collection Statement for Recruitment” before completing the application form.
  5. The CAiRS is an equal opportunity employer committed to diversity and inclusivity. All qualified applicants will received consideration for employment without regard to gender, ethnicity, nationality, family status or physical or mental disabilities.
  6. Applicants who are not invited to an interview within two months of the closing date should consider their applications unsuccessful.
© Centre for Advances in Reliability and Safety.