Senior Planning Research Scientist

We are a closely-knit team aspiring to change the world through disruptive technology. We are innovators. We are tinkerers. We are problem-solvers. And we have a fair amount of magic dust up our sleeves. We have a plan for fleet-level deployment of autonomous vehicles, and we are looking for the best-of-the-best to join us in making this a reality.

Based in the U.S. and Asia, Venti Technologies is the leader in safe-speed autonomous logistics systems, developing the future of goods transportation. Using rigorous mathematics, deep learning, and theoretically-grounded algorithms, Venti has a proprietary collection of autonomy technologies including a suite of powerful logistics algorithms. Venti’s proven value proposition of saving costs, increasing vehicle utilization, and improving safety is recognized by customers and driving growth. Launched in 2018, Venti brings together an unsurpassed team internationally. The company has autonomous systems deployed in Asia for industrial and logistics sites and a growing pipeline. Venti has offices in Cambridge (Massachusetts, USA), Suzhou (China), and Singapore – our Asian headquarters.

• Singapore

Position overview

We are seeking a Senior Planning Research Scientist with strong software engineering expertise to join our planning and control team. You will design, implement, and optimize advanced planning algorithms that enable autonomous vehicles to navigate complex and dynamic environments safely and efficiently.

In this role, you will own both the research and engineering aspects of planning — from developing novel algorithms to delivering clean, high-performance, and reliable C++ implementations ready for deployment. You will work cross-functionally with perception, prediction, and control teams to bring robust autonomy to large-scale operations.

Role responsibilities

• Algorithm & System Development: Design, implement, and maintain high-performance route planning and motion planning modules in modern C++. Deliver robust, efficient, and maintainable code for real-time autonomous driving applications.

• Performance Optimization: Profile and optimize planning algorithms for runtime efficiency, memory usage, and latency to meet real-time operational constraints.

• System Integration: Collaborate with perception, prediction, and control teams to ensure seamless data flow and performance consistency across the autonomy pipeline.

• Simulation and Testing: Implement, simulate, and validate planning algorithms in both simulation environments and real-world autonomous platforms. Conduct in-depth analysis to ensure robustness and reliability.

• System Debugging & Deployment: Debug complex, multi-module systems, analyze logs and telemetry, and ensure successful deployment of planning modules in both simulated and real-world environments.

• Collaboration & Mentorship: Work closely with fellow engineers and researchers, share best practices in system design, and mentor junior developers to strengthen engineering excellence within the team.

Required experience

• Educational Background: Ph.D. or Master’s degree in Computer Science, Robotics, Engineering, or a related field.

• Programming Proficiency: Strong proficiency in C++. Solid understanding of object-oriented programming, data structures, algorithms, and real-time software design.

• Algorithmic Knowledge: Strong foundation in graph search, sampling-based, and optimization-based methods, and familiarity with decision-making frameworks (FSMs, behavior trees).

• Experience with Optimization: Proven ability to optimize code for performance and resource constraints in real-time environments.

• Software Development Experience: Hands-on experience in developing large-scale robotic or autonomous systems. Proficiency with Linux, ROS/ROS2, Git, CMake/Bazel, and CI/CD pipelines.

• Leadership and Mentorship: Experience leading technical projects, mentoring engineers, and contributing to organizational growth.

• System Thinking: Understanding of how planning interacts with perception, localization, and control. Ability to reason about system-level trade-offs.

• Collaboration: Effective communicator who can work across disciplines and translate algorithmic concepts into software components that meet product requirements.