Staff Planning Research Scientist

VENTI TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Venti Technologies Pte. Ltd. in Singapore seeks a Staff Planning Research Scientist to steer the planning module of the autonomy stack, defining roadmaps and guiding algorithmic innovation across perception, prediction, and control.

You will mentor researchers, validate ideas in simulation and real deployments, and translate theory into robust, production-ready planning systems that are safe, efficient, and scalable.

Qualifications

• Ph.D. or Master’s in CS/Robotics with focus on planning or autonomous systems.
• Strong background in planning algorithms and decision-making frameworks.
• Experience with real-world autonomous systems and ROS is required.

Responsibilities

• Define long-term research and development roadmap for planning within the autonomy stack.
• Design, analyze, and validate advanced routing, behavior, and motion planning algorithms.
• Lead integration of planning with perception, prediction, localization, and control systems.
• Evaluate research trends and guide ideas to production-ready systems.
• Establish methods to evaluate planning performance under real-world conditions.
• Provide technical guidance to researchers and engineers.

Skills

Planning algorithms

ROS

System integration

Leadership

Communication

Education

Ph.D. or Master's in CS/Robotics

Tools

Gazebo

PyTorch

Job description

Position Overview

We are seeking a Staff Planning Research Scientist to lead the technical direction and system architecture for planning within our autonomy stack. In this role, you will drive the research roadmap, guide algorithmic innovation, and define how planning interacts with perception, prediction, and control systems to achieve safe, efficient, and scalable autonomy.

You will be responsible for identifying high-impact research directions, validating novel approaches through simulation and deployment, and mentoring the team to translate advanced theory into robust, real-world systems. This is a high-influence position suited for an individual who thrives at the intersection of deep technical research and system-level autonomy design.

Role Responsibilities

• Technical Leadership: Define the long-term research and development roadmap for planning within the autonomy stack. Identify key challenges in decision-making, trajectory generation, and optimization for real-world logistics operations.
• Algorithm Development: Design, analyze, and validate advanced route, behavior, and motion planning algorithms. Push the boundaries of autonomous planning through novel approaches in optimization, learning, and uncertainty modeling.
• System Integration: Lead integration of planning algorithms with perception, prediction, localization, and control systems. Anticipate system-level trade-offs and guide architectural decisions for reliable deployment.
• Research to Deployment: Evaluate academic and industrial research trends, prototype promising ideas, and guide their evolution into production-ready systems. Balance long-term research innovation with near-term deployment needs.
• Performance and Robustness Analysis: Establish methods to evaluate planning performance under complex and uncertain real-world conditions. Identify bottlenecks and develop strategies to enhance reliability, safety, and efficiency.
• Mentorship and Team Development: Provide technical guidance to researchers and engineers, fostering a culture of innovation, ownership, and delivery.
• External Awareness: Stay informed on advances in planning, decision-making, and learning for autonomy. Represent Venti in research discussions, conferences, and technical collaborations where appropriate.

Required Experience

• Educational Background: Ph.D. or Master’s degree in Computer Science, Robotics, Engineering, or a related field, with a focus on route planning, motion planning, or autonomous systems.
• Deep Planning Expertise: Mastery of planning algorithms (graph search, sampling-based, and optimization-based methods), route planning, and decision-making frameworks (behavior trees, FSMs, RL).
• Theoretical Foundations: Strong background in optimization, probabilistic reasoning, or control theory. Proven ability to formulate and solve complex autonomy problems using rigorous mathematical principles.
• Experience with Real-world Systems: Hands‑on experience with ROS (Robot Operating System) and real-world deployment of autonomous systems or robots.
• Leadership and Mentorship: Experience leading technical projects, mentoring engineers, and contributing to organizational growth.
• Collaboration & Communication: Excellent communication skills for working across multidisciplinary teams and influencing technical direction.