Lead Data Science (LLM & NLP, AI & ML)

Job Responsibilities

• Deliver high quality Large Language Model based information science solutions and AI/ML infrastructure to support new product development (NPD) in TE 
• Develop or adopt innovative AI techniques (using in-house coding tools or commercial software) and develop machine learning algorithms to deliver search and synthesis of internal and external data.  
• Collaborate with multi-disciplinary specialists in data science, electronics, material science, mechanics, additive manufacturing, and other fields.
• Work with local and global TE sites, and external customers/vendors, to address urgent or strategic needs.
• Partner with Singapore Research Institutes and universities to develop advanced AI techniques.
• Develop and execute TE’s roadmap and strategy for AI, specifically in the area of LLM. 
• Enhance the awareness across TE of the AI capabilities of the Singapore center and promote the democratization of AI across the TE engineering community.

Job Requirements: 

• Degree in Engineering (or related) with 8+ years relevant working/research experience in software development.
• A deep knowledge of data science and machine learning (a second degree in data science is a plus).
• Experience in R&D with a proven track record of technical leadership and execution.
• Strong multitasking, prioritization, and ability to delegate where appropriate and keep resources aligned with critical priorities.
• Strong verbal and written communication, and presentation skills with interpersonal skills to work with multiple level and multi-discipline stakeholders.
• Experience of training, evaluating and deploying Large Language Models (LLM) 
• Hands-on experience of data science and machine learning algorithms involving multiple data types
• Strong SW development skills including:
  • Python, Pytorch, Tensorflow
  • Rapid PoC development
  • Web App Development Frameworks such as Java, .Net etc
  • Windows App Dev eg: C++
  • Cloud compute AWS / Azure 
  • Rest API development / use
  • Hugging Face LLMs
  • CUDA / GPU computing.

Also beneficial:  

• Familiarity with some or all of the following: Additive Manufacturing, material development, electronic subsystem development, RF, signal integrity, product design.
• Knowledge of TE’s business, products, material and manufacturing processes 
• General background knowledge of material properties (mechanical, electric, thermal, etc.) including polymers and metals.
• Familiarity with Agile development techniques.