{"id":59729,"url":"https://alion.io/job/simbe-robotics-senior-computer-vision-applied-ai-engineer","title":"Senior Computer Vision / Applied AI Engineer","company":{"id":8498,"name":"Simbe Robotics","domain":"simberobotics.com","url":"https://alion.io/company/simbe-robotics","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":0.8,"repost_share":0,"time_to_fill_p50_days":83,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"CVAT","optional":false},{"name":"Data Augmentation","optional":false},{"name":"Edge AI","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OCR","optional":false},{"name":"ONNX","optional":false},{"name":"Perception","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Quantization","optional":false},{"name":"Roboflow","optional":false},{"name":"ROS","optional":false},{"name":"ROS2","optional":false},{"name":"Synthetic Data","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"TensorRT","optional":false}],"status":"live","first_seen_at":"2026-08-05T20:56:02Z","employer_posted_date":"2026-08-05","last_verified_at":"2026-10-16T08:03:42Z","board_verified":true,"closed_at":null,"days_open":71,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":71},"description":"Simbe is building the AI powered operating system for physical retail. Our autonomous robots and multimodal computer vision platform turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and customer focused product design to help retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity.\nSimbe is looking for a Senior Computer Vision / Applied AI Engineer to build production AI systems that turn store imagery into trusted retail intelligence. This role will work across dense product detection, price tag and promo tag detection, OCR, barcode decoding, product association, segmentation, visual search, model evaluation, and customer specific model improvements. The right person isa strong ML engineer, an exceptional software engineer, and a practical builder who enjoys messy real world data, rapid iteration, and measurable customer impact.\nWhy This Role Is High Impact\nYou will work on dense, cluttered, real world visual scenes where accuracy directly drives customer value.\nYou will help improve core Simbe use cases such as out of stock detection, price accuracy, promo compliance, top stock, and product location intelligence.\nYou will work on the full model lifecycle: data, annotation quality, training, evaluation, release, monitoring, and production debugging.\nResponsibilities\nBuild production CV models. Design, train, validate, and deploy models for object detection, segmentation, OCR, barcode localization, product recognition, shelf understanding, and other customer facing computer vision tasks.\nOwn dataset quality. Curate, clean, version, and analyze large real world training datasets, including hard negative mining, annotation QA, data audits, and active learning workflows.\nImprove model performance. Research and implement model architecture, loss function, data augmentation, synthetic data, and evaluation improvements that increase precision, recall, latency, and robustness across customers.\nSupport model releases. Contribute to model validation, release gates, inference wrappers, ONNX/TensorRT exports, and production monitoring so models are reliable in customer environments.\nDevelop tooling. Build internal tools for model evaluation, annotation review, error mining, data visualization, dataset exports, and deployment readiness.\nPartner cross functionally. Work closely with Product, Customer Success, Data, Robotics Software, and Field Operations to turn customer issues into model and pipeline improvements.\nStay current. Track modern work in open vocabulary detection, promptable segmentation, multimodal product understanding, visual search, OCR, and edge inference, and evaluate where it can create value for Simbe.\nRequired Qualifications\n5+ years of experience in computer vision, applied machine learning, robotics perception, or related production AI systems.\nStrong Python experience and hands on experience with PyTorch or TensorFlow.\nDemonstrated experience using AI-assisted coding and automation tools to accelerate software development, debugging, experimentation, and engineering workflows, with strong judgment around validating and reviewing AI-generated output. \n\nExperience training and evaluating object detection, segmentation, OCR, visual search, or image recognition models.Strong understanding of dataset curation, annotation quality, model evaluation, error analysis, and experimentation.\n\nExperience building maintainable production code and data pipelines in a Linux based environment.\nAbility to balance research quality with production constraints such as latency, compute, memory, robustness, and ease of deployment.\nStrong communication skills and a customer value mindset.\nBonus Qualifications\nExperience with retail, product recognition, shelf intelligence, OCR, barcode decoding, fine grained recognition, or visual product search.\nExperience with ONNX, TensorRT, CUDA, quantization, model profiling, or edge deployment.\nExperience with C++, ROS/ROS2, RGBD cameras, 3D geometry, homography, calibration, or robotic perception.\nExperience with FiftyOne, CVAT, Labelbox, Roboflow, or other data centric ML tools.\nExperience with synthetic data generation, simulation, active learning, or automated annotation workflows.\nPublications, patents, open source contributions, or production systems in relevant CV/AI 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