{"id":1266501,"url":"https://alion.io/job/meril-life-sciences-private-limited-senior-computer-vision-engineer","title":"Senior Computer Vision Engineer","company":{"id":3808095,"name":"Meril Life Sciences","domain":"merai.co","url":"https://alion.io/company/meril-life-sciences-private-limited-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vapi, 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take technical ownership of computer vision, optical tracking, camera calibration, and 6-DOF pose estimation for Immersive Technologies' next-generation Computer-Assisted Navigation solutions across workstation platforms.\n\nThe role will develop and validate robust optical tracking systems that convert camera observations, fiducial/marker information, and optical tracker measurements into accurate, stable, and time-synchronized 3D poses for surgical navigation.\n\nThe role requires a highly quantitative approach to computer vision engineering, with emphasis on detection reliability, pose stability, latency, reprojection error, coordinate-frame consistency, calibration, reacquisition, and regression-tested performance rather than subjective visual tuning.\n\nSkills and Competencies :\n\n- Strong proficiency in C++ and OpenCV.\n\n- Strong understanding of camera calibration and camera models.\n\n- Strong knowledge of PnP, rigid-body pose estimation, fiducial/marker detection, and optical tracking.\n\n- Strong understanding of 3D geometry and coordinate transformations.\n\n- Strong knowledge of homogeneous transformation matrices and multi-frame coordinate chains.\n\n- Strong understanding of camera-to-tracker, tracker-to-instrument, and tracker-to-anatomy transformations.\n\n- Experience with infrared cameras, optical tracking spheres, fiducial markers, or metrology systems.\n\n- Strong quantitative approach to computer-vision evaluation.\n\n- Experience measuring detection accuracy, pose jitter, latency, reprojection error, and tracking reliability.\n\n- Strong debugging skills across native C++, OpenCV, Android, and desktop environments.\n\n- Experience with JNI/NDK and native library integration is preferred.\n\n- Experience with Android Camera2 or desktop camera SDKs is preferred.\n\n- Experience with Python for offline computer-vision analysis and dataset processing is preferred.\n\n- Knowledge of RANSAC and geometric model fitting is preferred.\n\n- Knowledge of filtering and temporal pose stabilization techniques is preferred.\n\n- Experience with optical tracker calibration and system characterization is preferred.\n\n- Understanding of real-time processing, frame synchronization, timestamps, and latency management.\n\n- Strong analytical and problem-solving skills.\n\n- Strong attention to numerical accuracy, coordinate consistency, and measurement reliability.\n\n- Strong documentation and communication skills.\n\n- Ability to work effectively with software, hardware, embedded, biomechanics, clinical, and QA teams.\n\n- Comfortable working daily with physical cameras, optical trackers, instruments, fixtures, and laboratory navigation systems.\n\n- Passion for computer vision, surgical robotics, optical tracking, immersive technologies, and healthcare innovation.\nSkills\nComputer Vision, OpenCV, C++, Camera Calibration, Camera Systems, JNI, 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