Robotics Research Engineer - Social Navigation & VLA

Singapore Management University; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

Singapore Management University (SCIS) seeks a research-focused role in the School of Computing and Information Systems to advance robotics, social navigation, and VLA training. The position involves data collection, model training, and simulator integration within a small, agile academic team.

You will annotate data, optimize pipelines, and apply machine learning techniques to robot navigation challenges in a collaborative environment.

Qualifications

• Minimum Bachelor's/Master's degree in CS/IT/IS with focus on Robotics, Simulation, Social Pedestrian Modeling.
• Minimum 2 years of relevant research experience in robotics, social force modeling, simulation, robot navigation.
• Proficiency in Python and C++.
• Proven track record in robotics, simulation.
• Experience with machine learning for robotics, VLA training.
• Excellent working knowledge of Ubuntu and Linux command line.
• Ability to break down complex problems and design effective solutions.
• Innovating new approaches and thinking outside the box.
• Applicants with research publications in robotics advantageous.
• Ability to work cooperatively as part of a small, agile academic research team.
• Self-motivated and able to work independently and with a team.

Responsibilities

• Data acquisition setup and installation of hardware.
• Acquisition of robot data for social navigation.
• Annotation of training data.
• Starting and monitoring of model training.
• Integration of VLA models into robotics simulators.
• Finetuning of models.
• Other duties as assigned.

Skills

Python

C++

Robotics

Simulation

Machine Learning

Ubuntu/Linux

Education

Bachelor/Master in CS/IT/IS

Job description

Singapore Management University (SCIS) seeks a research-focused role in the School of Computing and Information Systems to advance robotics, social navigation, and VLA training. The position involves data collection, model training, and simulator integration within a small, agile academic team.

You will annotate data, optimize pipelines, and apply machine learning techniques to robot navigation challenges in a collaborative environment.