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Principal Robotics Engineer Bot Routing Jobs in Texas

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Principal Robotics Engineer Bot Routing information

What does a Principal Robotics Engineer specializing in Bot Routing do?

A Principal Robotics Engineer specializing in Bot Routing is responsible for designing, developing, and optimizing the algorithms and systems that control how robots navigate and move through their environments. This includes creating efficient routing paths, coordinating multiple robots, and ensuring reliable and safe movement in complex settings like warehouses or manufacturing facilities. They often lead teams, set technical direction, and collaborate with software and hardware engineers to integrate routing solutions into robotics platforms. Their work directly impacts the efficiency and effectiveness of automated robotic systems.

How does a Principal Robotics Engineer specializing in bot routing typically collaborate with cross-functional teams to optimize autonomous system performance?

As a Principal Robotics Engineer focused on bot routing, you will regularly partner with software developers, hardware engineers, data scientists, and operations teams to design and refine routing algorithms for autonomous robots. Collaboration often involves joint problem-solving sessions to address route efficiency, obstacle avoidance, and real-time system adaptation. You will also contribute technical leadership by mentoring junior engineers and ensuring that routing solutions align with broader project goals. This cross-disciplinary teamwork is essential for successfully deploying and scaling robotic solutions in dynamic environments.

What are the key skills and qualifications needed to thrive as a Principal Robotics Engineer in Bot Routing, and why are they important?

To thrive as a Principal Robotics Engineer in Bot Routing, you need advanced expertise in robotics, algorithm development, and systems engineering, typically supported by a graduate degree in robotics, computer science, or a related field. Proficiency with ROS (Robot Operating System), simulation tools like Gazebo, and experience with C++/Python programming are commonly required, along with relevant certifications. Strong leadership, problem-solving, and communication skills help in guiding multidisciplinary teams and coordinating complex projects. These skills are crucial for designing efficient routing algorithms, ensuring system reliability, and driving innovative robotics solutions in dynamic environments.

What is the difference between Principal Robotics Engineer Bot Routing vs Robotics Engineer?

AspectPrincipal Robotics Engineer Bot RoutingRobotics Engineer
CredentialsBachelor's/Master's in Robotics, Electrical, or Mechanical Engineering; experience with bot routing systemsBachelor's or higher in Robotics, Mechanical, Electrical Engineering; some experience with robotics systems
Work EnvironmentDesigning and overseeing complex bot routing algorithms in R&D or advanced manufacturingDeveloping and testing robotics applications in labs or field environments
Industry UsageUsed in automation, logistics, and manufacturing sectors for advanced routing solutionsApplied across various industries for general robotics development and implementation

The main difference is that Principal Robotics Engineer Bot Routing focuses on leading the design and optimization of bot routing systems, often in senior technical roles, while Robotics Engineers typically develop and implement robotics solutions at a more operational level. Both roles require strong technical skills, but the principal role involves higher-level oversight and strategic planning.

What are popular job titles related to Principal Robotics Engineer Bot Routing jobs in Texas? For Principal Robotics Engineer Bot Routing jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Principal Robotics Engineer Bot Routing jobs? Cities in Texas with the most Principal Robotics Engineer Bot Routing job openings:
Infographic showing various Principal Robotics Engineer Bot Routing job openings in Texas as of July 2026, with employment types broken down into 76% Full Time, 6% Part Time, 2% Contract, and 16% Nights. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution.

Machine Learning/Deep Learning Engineer(PhD, New Grad)

Bot Auto

Houston, TX

Other

Posted 8 days ago


Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

Key Responsibilities
  • Model Implementation & Iteration: Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including object detection, tracking, online mapping, and end-to-end planning.
  • Full Lifecycle Execution: Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.
  • Cross-Functional Collaboration: Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.
  • Literature Tracking: Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.
QualificationsRequired:
  • Education: An advanced degree (Master's or Ph.D., including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • Core Knowledge: Strong theoretical foundation in machine learning, deep learning, and computer vision, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).
  • Attributes: High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.
Preferred (Targeted Research & Background):
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • 3D Computer Vision / Bird's-Eye-View (BEV) Perception
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A proven track record of research publications in top-tier machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS) as a primary contributor.
  • Engineering Plus: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).
  • Industry Exposure: Prior internship experience within the autonomous driving industry or advanced robotics labs is highly desirable.