AI Engineer, AI Agent Development for AI Singapore

Company description:

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job description:

Job Description

AI Singapore (AISG) is a national AI programme launched by the National Research Foundation (NRF) to anchor deep national capabilities in Artificial Intelligence (AI).

The programme office is hosted by the National University of Singapore (NUS) and brings together all Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies developing AI products to perform use-inspired research, grow the knowledge, create the tools, and develop the talent to power Singapore's AI efforts.

This is an exciting opportunity for an AI Engineer to be at the forefront of AI innovation. You will design, build, and optimize real-time autonomous AI agents for immersive 3D game environments. This role involves a unique blend of cutting-edge research in computer vision, large language models (LLMs), and real-time action systems.

This position is pivotal in bridging state-of-the-art research with practical deployment, directly supporting AISG's mission to advance applied AI through impactful research and scalable product development. You will contribute to strengthening collaborations between AISG's applied research teams and our industry partners.

Duties and Responsibilities

• Architect, implement, and refine modular AI pipelines that support agent perception, planning, and action within real-time 3D environments.
• Develop and optimize real-time perception systems leveraging advanced computer vision models.
• Create and experiment with novel vision-language-action models for autonomous gameplay, drawing inspiration from robotics.
• Conduct research into multi-agent systems and cooperative/competitive behaviors within simulated environments.
• Integrate AI models into leading game engines (e.g., Unity, Unreal Engine) for interactive training, evaluation, and deployment.
• Design innovative reward functions and robust evaluation metrics for reinforcement learning agents.
• Curate and maintain high-quality datasets for supervised and self-supervised learning paradigms.
• Build and scale cloud-ready inference pipelines utilizing containerization (Docker, Kubernetes) and MLOps best practices.
• Perform rigorous latency optimization and benchmarking to ensure real-time system performance.
• Mentor junior team members and foster a collaborative development environment through constructive code reviews.
• Communicate research findings and project progress effectively through demos, internal presentations, and contributions to external academic forums where appropriate.
• Actively participate in cross-functional planning, project retrospectives, and knowledge-sharing initiatives

Qualifications

• A Master's or PhD degree in Computer Science, Artificial Intelligence, Robotics, or a closely related field.
• Strong programming proficiency in Python and C++.
• Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow).
• Hands-on experience with simulation environments such as Unity ML-Agents, NVIDIA Isaac Sim, Mujoco, or similar.
• Solid expertise in computer vision techniques, transformer architectures, and multi-modal learning.
• Familiarity with reinforcement learning (RL) principles, curriculum learning strategies, and the challenges of real-time systems.
• Working knowledge of distributed systems and container technologies (e.g., Docker, Kubernetes).
• Excellent communication and collaboration skills, with an ability to articulate complex technical concepts to diverse audiences.
• A genuine passion for developing AI agents for 3D environments (e.g., gaming, simulation) and a strong alignment with AISG's mission.

More Information

Location: Kent Ridge Campus

Organization: Office of the Deputy President(Res&Tech)

Department : AI Singapore

Employee Referral Eligible: No

Job requisition ID : 29209