Peppermint Robotics

Robotics Perception Engineer - SLAM
Location: Pune, India&nbsp;
Job Type: Full-Time
About Us
Peppermint Robotics is an autonomous robotics company based out of Pune, India. Started in 2019 at SINE IIT Bombay, we have grown into a leader in commercial cleaning and industrial material handling robots, with operations in six countries. With offices in Pune, Dubai, and Austin, we are a passionate, engineering-driven team tackling hard robotics problems—from real-time localization to robust navigation.
Our Mission: At Peppermint Robotics, our mission is to build intelligent robots that automate repetitive and mundane tasks, freeing humans to focus on higher-value work and unlocking greater human potential.
Role Overview
We are seeking a Robotics Perception Engineer - SLAM to join our core autonomy team in Pune. This role focuses on developing and optimizing 3D LiDAR-based SLAM solutions, enabling reliable and accurate localization and mapping for autonomous robots deployed across complex, real-world environments. We are looking for engineers who are not only experts in robotics but also proficient in using modern AI tools like Claude or Gemini to accelerate software development and code generation.
Responsibilities
<ul>
<li>
SLAM System Development: Develop robust, real-time SLAM systems using 3D LiDARs and other onboard sensors.
</li>
<li>
Optimization: Design and implement factor graph-based optimization pipelines using GTSAM, Ceres Solver, G2O.
</li>
<li>
Sensor Fusion: Integrate SLAM with IMU, wheel odometry, and vision-based systems for sensor fusion.
</li>
<li>
AI-Augmented Engineering: Leverage advanced AI models (e.g., Claude, Gemini) for efficient code generation, debugging, and algorithm optimization.
</li>
<li>
Testing &amp; Validation: Continuously test and validate SLAM modules across diverse real-world deployments—including crowded airports, large malls, and hospitals.
</li>
<li>
Cross-Functional Collaboration: Collaborate closely with perception, controls, and navigation teams to ensure seamless robot autonomy.
</li>
<li>
Performance Tuning: Profile and optimize SLAM performance for resource-constrained embedded compute platforms.
</li>
</ul>
QualificationsMinimum Qualifications
<ul>
<li>
Education: Bachelor’s degree in Robotics, Computer Science, Electrical Engineering, or a related field.
</li>
<li>
Experience: 2+ years of hands-on experience developing SLAM systems for autonomous robots.
</li>
<li>
Domain Expertise: Proven expertise with 3D LiDAR-based SLAM in large, dynamic indoor environments.
</li>
<li>
Theoretical Knowledge: Strong grasp of probabilistic estimation, sensor fusion, and graph optimization.
</li>
<li>
Programming: Proficient in C++ and Python in a Linux-based development environment.
</li>
<li>
Optimization Tools: Experience with GTSAM, iSAM2, Ceres Solver, or G2O.
</li>
<li>
Middleware: Familiarity with ROS/ROS2 and standard robotics middleware.
</li>
<li>
AI Proficiency: Demonstrated ability to use LLMs (Claude or Gemini) to accelerate software development and solve complex technical challenges.
</li>
<li>
Real-world Impact: A track record of deploying SLAM solutions in real-world applications.
</li>
</ul>
Preferred Qualifications
<ul>
<li>
Advanced Mapping: Experience with loop closure, global mapping, and multi-session SLAM.
</li>
<li>
Point Cloud Processing: Familiarity with PCL, Open3D, or similar libraries.
</li>
<li>
Research &amp; Community: Contributions to open-source SLAM projects or publications in leading conferences (e.g., ICRA, IROS, RSS).
</li>
<li>
Embedded Systems: Knowledge of performance optimization on resource-constrained hardware.
</li>
</ul>