{"id":760494,"url":"https://alion.io/job/origin-lead-perception-engineer","title":"Lead Perception Engineer","company":{"id":686527,"name":"Origin","domain":"origin.tech","url":"https://alion.io/company/origin-7","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":95,"open_postings":22,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":60,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Robotics","role_family":"Robotics","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":64000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":46},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Path Planning","optional":false},{"name":"Python","optional":false},{"name":"Self-Healing","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"GStreamer","optional":true},{"name":"OpenCV","optional":true},{"name":"PyTorch","optional":true},{"name":"PyTorch C++","optional":true},{"name":"ROS","optional":true},{"name":"ROS2","optional":true},{"name":"SLAM","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-07-23T00:00:00Z","employer_posted_date":"2026-07-23","last_verified_at":"2026-10-17T19:14:59Z","board_verified":true,"closed_at":null,"days_open":86,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":86},"description":"About Origin\nOrigin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver 5x faster execution, 250%+ margin expansion, and significant cost savings. Join India’s most talent-dense robotics team consisting of individuals from IITs, Stanford, UCLA, etc.\nAbout the Role\nYou will work on building and optimizing 3D perception systems that enable robots to understand and interact with complex real-world environments. The goal is to develop robust perception pipelines that work reliably across both simulation and real-world construction sites, ensuring accurate scene understanding, localization, and decision-making.\nKey Responsibilities\n3D Perception Development & Scene Understanding\nDesign, implement, and deploy realtime 3D perception pipelines leveraging LiDAR, IMU, Stereo, and RGB cameras.\nDevelop algorithms for spatial and temporal data interpretation to enable high-fidelity semantic scene understanding.\nOptimize ego-motion estimation and localization modules to ensure seamless integration with downstream planning and control tasks.\nDeep Learning\nTrain and integrate deep learning models required for semantic world understanding and surface finish classification for quality control\nCollect and curate high-quality datasets (real and synthetic) and automate training pipelines and experiment tracking.\nBenchmark and optimize perception models for edge devices to ensure real-time performance in resource-constrained environments\nSensor Fusion & Localization\nDesign and implement sensor fusion strategies combining visual, inertial, and spatial data\nArchitect and implement sophisticated sensor fusion strategies that integrate classical methods with deep learning approaches to convert noisy, asynchronous data from heterogeneous sensors into a unified environment representation.\nCalibration\nDevelop and automate robust extrinsic and intrinsic calibration procedures (Camera, LiDAR, IMU) using target-based and/or targetless methods.\nDesign and implement algorithms for online calibration drift detection and self-healing to maintain system integrity during long-term deployments.\nEstablish rigorous quantitative metrics to objectively evaluate and certify calibration quality.\nCollaboration\nPartner with Navigation, Manipulation, and Cloud teams to ensure perception outputs are optimized for downstream path planning, grasping, and remote fleet monitoring.\nDefine, track system-level and own system level KPIs and perception metrics to identify regressions across software iterations.\nRequirements\n5+ YoE\nStrong fundamentals in computer vision and 3D perception\nProficiency in C++ (Python is a plus)\nFamiliarity with PyTorch, TensorRT\nBasic understanding of Localisation and SLAM\nAbility to work with real-world data and debug complex systems\nNice to Have\nExperience with Nvidia Deepstream, GStreamer, Holoscan\nExperience with ROS/ROS2\nHands-on experience with LiDAR, RGB-D cameras, or IMUs\nFamiliarity with OpenCV, PCL, or similar libraries\nExperience working on robotics or vision-based 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