Research Engineer (Machine Learning)

Nanyang Technological University; Singapore; On-site; SGD 80,000 - 140,000; Full time

Job summary

NTU Singapore is seeking a Research Engineer to design, implement, and integrate Visual-Language Models into autonomous mobile robot platforms. You will enable semantic reasoning and perception–language grounding, interfacing with navigation and control pipelines for end-to-end experimentation.

The role involves building simulation environments, conducting GPU-enabled experiments, and supporting rapid prototyping from concept to real-world deployment.

Qualifications

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical or Mechanical Engineering, or a related discipline.
• Proficiency in Python, with experience in ROS/ROS2 and Linux-based development environments.
• Familiarity with robotic simulation platforms and 3D modelling tools.
• Hands-on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus.
• Strong problem-solving ability, collaborative and independent work style, willingness to learn new tools.

Responsibilities

• Design, implement, and integrate VLMs into simulation and robotic platforms for semantic reasoning and decision-making.
• Interface VLM modules with navigation, mapping, localization, planning, and control systems for end-to-end autonomy.
• Build and maintain simulation environments, multimodal datasets, and evaluation frameworks with large data volumes.
• Conduct GPU-enabled experiments for model training, inference, and simulation-based evaluation.
• Support rapid prototyping and iteration from concept to validated robotic systems.
• Collaborate with research staff and students across multiple projects.
• Contribute to research outputs, including publications, technical disclosures, patents, and demonstrations.
• Promote reproducibility and maintainability in research software.

Skills

Python

ROS/ROS2

Linux

3D modelling

Autonomous robotics

Problem-solving

Education

Bachelor’s or Master’s in Robotics/CS/EE/Mech Eng

Tools

simulation platforms

Job description

We are seeking a Research Engineer to design, implement, and integrate Visual-Language Models (VLMs) into autonomous mobile robots platform. The role focuses on enabling high-level semantic reasoning, perception–language grounding, and decision-making in robotic systems. The engineer will interface VLMs with navigation, mapping, and control pipelines to support end-to-end system experimentation. Responsibilities include building simulation environments, conducting experimental evaluations, and supporting rapid prototyping. The role contributes to translating simulation-validated methods toward real–world robotic deployment and bridges robotics simulation, multimodal AI, and autonomous navigation research.

Key Responsibilities

• Design, implement, and integrate Visual-Language Models (VLMs) into simulation and robotic platforms to enable semantic reasoning, perception–language grounding, and decision-making.
• Interface VLM-based modules with robot navigation, mapping, localization, planning, and control systems to support end-to-end autonomous operation.
• Build and maintain simulation environments, multimodal datasets, and evaluation frameworks, handling data volumes from tens to hundreds of gigabytes.
• Conduct experimental studies using GPU-enabled computing resources for model training, inference, and simulation-based evaluation.
• Support rapid prototyping and iteration of research ideas, from concept to validated robotic systems and demonstrations.
• Collaborate with and provide technical support to research staff and students across multiple projects.
• Contribute to research outputs, including publications, technical disclosures, patents, and autonomous robot demonstrations.
• Apply and recommend engineering best practices that promote reproducibility, maintainability, and research productivity.

Job Requirements

• Bachelor’s or Master’s degree (BEng/BSc/MEng/MSc) in Robotics, Computer Science, Electrical or Mechanical Engineering, or a related discipline; candidates with strong robotics and autonomous systems experience from other disciplines may also be considered.
• Proficiency in Python, with experience in ROS/ ROS2 and Linux-based development environments.
• Familiarity with robotic simulation platforms and 3D modelling tools.
• Hands‐on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus.
• Strong problem‐solving ability, collaborative and independent work style, willingness to learn new tools.

We regret that only shortlisted candidates will be notified.

Hiring Institution

NTU A research-intensive public university, Nanyang Technological University, Singapore (NTU Singapore) has 33,000 undergraduate and postgraduate students in the Engineering, Business, Science, Humanities, Arts, & Social Sciences, and Graduate colleges. It also has a medical school, the Lee Kong Chian School of Medicine, established jointly with Imperial College London. NTU is also home to world‑class autonomous institutes – the National Institute of Education, S Rajaratnam School of International Studies, Earth Observatory of Singapore, and Singapore Centre for Environmental Life Sciences Engineering – and various leading research centres such as the Nanyang Environment & Water Research Institute (NEWRI) and Energy Research Institute @ NTU (ERI@N). Ranked amongst the world’s top universities by QS, NTU has also been named the world’s top young university for the past seven years. The University’s main campus is frequently listed among the Top 15 most beautiful university campuses in the world and has 57 Green Mark‑certified (equivalent to LEED‑certified) buildings, of which 95% are certified Green Mark Platinum. Apart from its main campus, NTU also has a campus in Novena, Singapore’s healthcare district. Under the NTU Smart Campus vision, the University harnesses the power of digital technology and tech‑enabled solutions to support better learning and living experiences, the discovery of new knowledge, and the sustainability of resources.

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