Professional Officer in Applied Artificial Intelligence (AI)

The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society.

The university’s unique pedagogy integrates work and study, embracing authentic learning in a real-world environment through collaborations with key strategic partners. Its focus on applied research with business impact is aimed at helping industry innovate and grow. SIT’s centralised campus within the Punggol Digital District features a vibrant learning environment where academia and industry are tightly integrated with the community.

SIT espouses an applied learning approach and offers degrees with a strong focus on science and technology. Our faculty work closely with industry on translational research and innovation, as well as provide consultancy on solutions to industry challenges. This well-established nexus with industry endows our graduates with deep skills and work-ready training experience – attuning them to the needs and demands of the future economy.

SIT is also establishing strategic live test beds known as ‘Living Labs’ both within and beyond its Punggol campus to support greater experiential learning and strengthen its applied research offerings. The university’s pool of experts works with multi-disciplinary teams to drive the horizontal technology enablers required to support SIT’s strategic translational research.

The Professional Officers Division (POD) houses a centralised pool of academic staff under the Professional Officers scheme. Professional Officers bring specialised and deep technical expertise developed through extensive industry experience. They provide a critical industry perspective to student learning and applied research, complementing the academic expertise of faculty by translating industry practices and real-world applications into the curriculum.

SIT is expanding its applied AI research capabilities, building a cohort of academic staff who are keen and experienced working on industry problems across sectors. Focus areas for applied AI include domains such as:

• • Advanced Manufacturing & Semiconductors
  • Urban Systems
  • AI-Augmented Engineering
  • AI Safety & Security
  • Chemical Engineering & Biotechnology
  • Hospitality and Tourism
  • Healthcare

Responsibilities:

• Design, develop, and teach laboratory sessions and practice-based modules in Applied AI and related areas.
• Lead or co-lead innovative applied research and industry collaboration projects with industry partners and government agencies.
• Secure and manage research grants to support applied research initiatives.
• Supervise and mentor students in applied research projects, Capstone Projects, and the Integrated Work Study Programme (IWSP).
• Manage laboratory facilities, equipment, and technical resources to support academic programmes and applied research activities.
• Ensure compliance with laboratory safety policies, procedures, and best practices.
• Contribute to the development of applied AI capabilities, learning resources, and industry-relevant curriculum support.
• Work closely with faculty and internal stakeholders to drive teaching, applied research, and innovation initiatives outcomes.

Qualifications:

• A good Bachelor’s degree or Master’s degree in Computer Science, Engineering, or a related discipline, with demonstrated experience in Artificial Intelligence (AI) / Machine Learning (ML) research or application. Equivalent industry experience may also be considered.
• At least 8 years of relevant industry experience, preferably in a technical role within an organisation driving research and/or innovation outcomes
• Strong technical expertise in one or more of the following areas:
  • Computer Vision and Image Processing
  • Machine Learning, Deep Learning, and Reinforcement Learning
  • Large Language Models (LLMs) and Multimodal Models
  • Generative AI, Agentic AI, Physical AI, and Embodied AI
  • Trustworthy AI, including explainability, auditability, and privacy
  • Edge AI and model optimisation
  • Physics-informed neural networks (PINNs) and surrogate modelling
  • Time-series modelling and anomaly detection
  • Bayesian methods and uncertainty quantification
  • Graph Neural Networks (GNNs)
  • Spatiotemporal data engineering
  • Digital twins and simulation
• Demonstrated experience applying AI to the SIT’s focus areas
• Experience in one or more of the following areas will be advantageous: Caffe, Spark ML, Keras, PyTorch, TensorFlow, Scikit-learn, CNTK, big data technologies such as Apache Hadoop and Spark, and DevOps/MLOps.
• Strong foundation in data structures, data modelling, and software architecture, with programming proficiency in Python, R, Java, and/or C/C++.
• Good grounding in mathematics, including probability, statistics, and algorithms.
• Demonstrated interest and capability in supporting research and academic project work, with the ability to develop software solutions to technical problems.
• Strong supervisory and mentoring skills, with an interest in working closely with students in an educational environment.
• Commitment to continuous learning and professional development, with the ability to keep abreast of developments in the field. Relevant industry certifications will be an added advantage.
• For senior appointments, demonstrated managerial or team leadership experience may be required.

Key Competencies

• Passion for teaching, coaching, and mentoring students and junior practitioners.
• Strong analytical and hands-on problem-solving skills.
• Ability to build and maintain effective working relationships with internal and external stakeholders.
• Adaptability and willingness to work across functions and teams in a dynamic environment.
• Self-motivated and committed to continuous learning and professional growth.
• Strong technical writing, communication, and presentation skills.
• Good analytical, critical thinking, and problem-solving abilities.
• Proactive, resourceful, and able to take ownership of assigned responsibilities.

What SIT offers:

• An applied research environment to tackle real-world problems together with industry partners
• Opportunities to shape a coherent applied AI research agenda with colleagues across disciplines and build Singapore’s applied AI research capability at a pivotal moment
• Access to SIT’s Living Lab Network and Punggol Digital District ecosystem as testbeds
• Singapore’s exceptional quality of life, competitive personal tax environment, and position as Asia’s leading research and innovation hub