Research Scientist, SLAM & VIO

Mecka AI is building the data infrastructure layer for robotics and embodied AI. They are seeking a Research Scientist (SLAM & Visual-Inertial Odometry) to build and validate state estimation systems that work in the real world, focusing on developing robust pipelines and algorithms for various visual odometry and SLAM tasks.

Responsibilities:

• Develop robust monocular VO/VIO pipelines (feature-based and/or learned) with strong failure detection and recovery
• Address scale ambiguity with inertial fusion, motion priors, and consistency constraints
• Online performance: low latency, bounded memory, and stable tracking across lighting, motion blur, rolling shutter, and dynamic objects
• Build offline reconstruction pipelines for long trajectories: global BA, loop closure at scale, and map optimization
• Produce high-quality trajectories and sparse/dense maps for downstream data products (labeling, QA, training signals)
• Design evaluation tooling: drift decomposition, per-segment error, and systematic bias detection
• Implement stereo VO/VIO with accurate calibration handling (intrinsics/extrinsics, temporal sync) and robust matching
• Improve depth reliability across challenging scenes (low texture, repetitive patterns, specularities)
• Optimize for stability and long-duration runs: track health metrics, relocalization, and graceful degradation
• Large-scale mapping and trajectory refinement using stereo constraints
• Loop closure + global pose graph optimization with principled uncertainty handling
• Produce maps that are useful, not just pretty: consistent frames, repeatable landmarks, and clear quality scores
• Sensor modeling & calibration: rolling shutter, time offsets, IMU noise/scale factors, and temperature-driven drift
• Robustness engineering: automatic resets, outlier handling, and 'what broke?' diagnostics
• Metrics & datasets: design evaluation suites, curate failure cases, and define release gates