Job Description
Job Title: SLAM Expert
Location: Vapi, Gujarat
Employment Type: Full-Time
Overview
We are seeking a skilled SLAM Expert responsible for localization and mapping, including visual(-inertial), Li DAR, and multi-sensor fusion, as well as dense and semantic mapping. The role involves developing robust SLAM systems for various robotics platforms.
Key Responsibilities
Architect multi-modal SLAM systems (VIO/LIO/VLIO) with loop closure and relocalization.
Build scalable map stores, implement change detection, and support lifelong mapping.
Ensure tight integration with perception (semantic) and planning (topological/metric) modules.
Collaborate with cross-functional teams to deploy SLAM in real-world robotic systems.
Must-Haves
2–3+ years of experience in SLAM or related domains.
Strong programming skills in C++/Rust and CUDA.
Expertise in factor graphs, optimization, and observability analysis.
Ability to ensure robustness to dynamics, low-texture environments, and varying lighting/weather conditions.
Nice-to-Haves
Experience with multi-robot SLAM and cloud mapping.
Knowledge of GNSS/RTK fusion.
Familiarity with HD maps and lane-level precision for automotive applications.
Success Metrics
Absolute Trajectory Error (ATE) / Relative Pose Error (RPE).
Relocalization latency.
Map freshness and size.
System failure rate.
Domain Notes
Humanoids:
- Handheld/tool tracking indoors.
AGVs (Autonomous Ground Vehicles):
- Operation in GNSS-denied environments, reflective floors, and pallet occlusions.
Cars:
- HD/L3 mapping with lane-level precision.
Drones:
- GPS-denied VIO, loop closure at altitude.
Application Instructions
Interested candidates may apply by sending their resume and cover letter to with the subject line: “SLAM Expert Application”.
Location: Vapi, Gujarat
Employment Type: Full-Time
Overview
We are seeking a skilled SLAM Expert responsible for localization and mapping, including visual(-inertial), Li DAR, and multi-sensor fusion, as well as dense and semantic mapping. The role involves developing robust SLAM systems for various robotics platforms.
Key Responsibilities
Architect multi-modal SLAM systems (VIO/LIO/VLIO) with loop closure and relocalization.
Build scalable map stores, implement change detection, and support lifelong mapping.
Ensure tight integration with perception (semantic) and planning (topological/metric) modules.
Collaborate with cross-functional teams to deploy SLAM in real-world robotic systems.
Must-Haves
2–3+ years of experience in SLAM or related domains.
Strong programming skills in C++/Rust and CUDA.
Expertise in factor graphs, optimization, and observability analysis.
Ability to ensure robustness to dynamics, low-texture environments, and varying lighting/weather conditions.
Nice-to-Haves
Experience with multi-robot SLAM and cloud mapping.
Knowledge of GNSS/RTK fusion.
Familiarity with HD maps and lane-level precision for automotive applications.
Success Metrics
Absolute Trajectory Error (ATE) / Relative Pose Error (RPE).
Relocalization latency.
Map freshness and size.
System failure rate.
Domain Notes
Humanoids:
- Handheld/tool tracking indoors.
AGVs (Autonomous Ground Vehicles):
- Operation in GNSS-denied environments, reflective floors, and pallet occlusions.
Cars:
- HD/L3 mapping with lane-level precision.
Drones:
- GPS-denied VIO, loop closure at altitude.
Application Instructions
Interested candidates may apply by sending their resume and cover letter to with the subject line: “SLAM Expert Application”.
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