Lead multiple strategic, cross-functional projects that apply data science and AI to new product development, product design, manufacturing process development, material formulation, testing, and other engineering workflows.
Develop and guide advanced AI/ML solutions using experimental, simulation, CAD, manufacturing, and enterprise engineering data, including surrogate modeling, optimization, inverse design, computer vision, generative design, and other appropriate techniques.
Develop agentic AI solutions for engineering use cases, including workflow and multi-agent orchestration, as well as integration with engineering tools and data sources such as CAD/CAE, simulation, PLM and internal knowledge systems.
Establish evaluation and validation approaches for existing commercial AI solutions, including model performance, robustness, uncertainty, engineering/physics consistency, safety, guardrails, traceability, and business impact.
Work in a multi-disciplinary environment with specialists in data science, mechanical engineering, material science, mechanics, additive manufacturing, software engineering, and other fields.
Collaborate with multiple business units to identify high-value opportunities, define requirements and deliverables, make technical trade-offs, and drive projects from problem definition through validation and implementation.
Create awareness across TE of the AI modeling and agentic AI capabilities of the Singapore center and support adoption of reusable methods and best practices across engineering teams.
Work with local and global TE sites, external customers, technology partners, and research institutes to address urgent or strategic needs, develop advanced AI techniques, validate results, and enable effective knowledge transfer.
Job Requirements
Advanced degree in Mechanical Engineering, Computational Engineering, Applied Mechanics, Data Science, Artificial Intelligence, or a closely related field. Typically, PhD with 4+ years, Master degree with 7+ years, or Bachelor degree with 10+ years of relevant industrial/research experience.
Demonstrated track record of independently leading technically complex R&D or engineering AI projects and delivering measurable impact in product development, simulation, manufacturing, materials, or related engineering domains.
Deep understanding of data science and artificial intelligence, including machine learning model development, feature/data engineering, validation, optimization, and the ability to select appropriate algorithms and architectures for engineering problems.
Hands-on knowledge of generative AI and agentic AI concepts and technologies, such as large language models (LLMs), RAG, embeddings/vector search, tool/function calling, agent orchestration and secure integration with enterprise or engineering systems.
Broad understanding of multiphysics simulation such as finite element analysis, together with practical experience in CAD and engineering design workflows; experience with generative or AI-assisted design is highly desirable.
Strong programming skills in Python or similar languages and hands-on experience with commonly used data science/ML frameworks and software development practices.
Broad knowledge of manufacturing processes, material behavior, product design, and the relationship between physical engineering constraints and data-driven/AI models.
Strong project leadership and stakeholder management skills, with experience working across functions, business units, and geographically distributed teams.
Strong communication skills with the ability to explain complex AI concepts, technical risks, and recommendations to both engineering specialists and senior stakeholders.
Preferred
Familiarity with TE products (connectors, cables, sensors, etc.) and manufacturing processes such as molding, extrusion, plating, stamping, and assembly.
Experience integrating AI with engineering software or enterprise systems, including CAD/CAE tools, simulation platforms, APIs, databases, cloud or on-premise AI platforms, and containerized deployment.
Experience with MLOps/LLMOps, model and agent evaluation frameworks, data governance, security, and enterprise deployment of AI solutions.
Track record of technical publications, patents/invention disclosures, externally funded research, or collaboration with universities/research institutes.
Familiarity with project management and software collaboration tools.
Competencies
Values: Integrity, Accountability, Inclusion, Innovation, Teamwork
Job Locations
UE SQUARE, 83 CLEMENCEAU AVENUE
Singapore, Central Singapore 239920
Singapore
Posting City
Singapore
Job Country
Singapore
Travel Required
Less than 10%
Requisition ID
158577
Workplace Type
Onsite
External Careers Page
Engineering & Technology
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