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.

Position overview

We are seeking a highly skilled and motivated Senior Planning Research Scientist to join our planning and control team. As part of this team, you will work on cutting-edge research and development of planning algorithms that enable autonomous systems to navigate complex environments safely and efficiently. This is an exciting opportunity for individuals who are passionate about advancing the field of autonomy and robotics. You will play a key role in the design, development, and optimization of behavior and motion planning systems while collaborating closely with cross-functional teams.

Role responsibilities

• Technical Leadership: Define and drive the technical roadmap for planning within the autonomy stack, ensuring alignment with product milestones and deployment goals.

• Algorithm Development: Design and develop advanced route planning/route optimization algorithm, and behavior and motion planning algorithms for autonomous vehicles, focusing on trajectory generation to ensure safe and efficient navigation in dynamic environments.

• 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.

• 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.

• Optimization: Optimize existing behavior and motion planning algorithms for enhanced performance, scalability, safety, and energy efficiency. Identify bottlenecks and propose solutions to improve real-time planning.

• Mentorship and Team Development: Provide technical guidance to researchers and engineers, fostering a culture of innovation, ownership, and delivery.

• Innovation for Deployment: Anticipate long-term challenges in autonomous driving (e.g., safety validation, fleet scalability, corner case handling) and propose practical solutions that accelerate product readiness.

• Cross-Functional Collaboration: Partner with engineering and product teams to translate high-level requirements into planning capabilities that support commercial deployment.

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.

• Programming Proficiency: Strong proficiency in C++. Experience with software development for large-scale 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).

• Experience with Optimization: Demonstrated ability to optimize algorithms for performance and efficiency in real-time systems.

• 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.

• Problem-Solving Mindset: Ability to identify product-critical challenges, balance trade-offs, and deliver scalable solutions under real-world constraints.