{"id":1803803,"url":"https://alion.io/job/infosys-computer-vision-engineer-4","title":"Computer Vision Engineer","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":95,"open_postings":268,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-07T05:47:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Ansible","optional":false},{"name":"Computer Vision","optional":false},{"name":"Configuration Management","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"Neo4j","optional":false},{"name":"ONNX","optional":false},{"name":"PyTorch","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Transformers","optional":false},{"name":"Triton","optional":false}],"status":"live","first_seen_at":"2026-09-28T18:17:36Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-08T00:51:59Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"We are seeking a highly skilled Computer Vision Engineer with hands-on experience in developing and deploying deep learning models for real-time image and video analytics. The ideal candidate will have a strong background in computer vision, deep learning frameworks, and edge deployment technologies.\nResponsibilities\nDesign, train, and optimize deep learning models for computer vision tasks such as object detection, image recognition, segmentation, and video analytics.\nLead large-scale real-time implementations involving 100+ video streams.\nFine-tune models like CNNs and Vision Transformers using frameworks such as TensorFlow, PyTorch, and ONNX.\nBuild and deploy inference pipelines using NVIDIA technologies including NGC models, TAO Toolkit, DeepStream Metropolis, and Triton Server.\nApply pre- and post-processing techniques to enhance model performance and evaluation.\nDevelop and implement multi-object tracking algorithms across multiple camera feeds., Perform camera calibration and extract regions of interest (ROI), action recognition using temporal analysis techniques.\nDevelop models for feature extraction and come up with strategies for latent space analysis and manipulation of the data.\nProficiency in writing complex SQL queries, familiarity with NoSQL or Graph Databases (Neo4j) is an advantage.\nKnowledge of infrastructure as code tools (e.g., Terraform, Ansible) is an advantage.\nProficiency with containerization technologies (Docker) and orchestration tools (Kubernetes) is an advantage.\nAdditional responsibilities\nGood knowledge on software configuration management systems\nStrong business acumen, strategy and cross-industry thought leadership\nAwareness of latest technologies and Industry trends\nLogical thinking and problem solving skills along with an ability to collaborate\nTwo or three industry domain knowledge\nUnderstanding of the financial processes for various types of projects and the various pricing models available\nClient Interfacing skills\nKnowledge of SDLC and agile methodologies\nProject and Team management\nPreferred skills\nTechnology->AI-Data science->Computer Vision,Technology->AI-Data science->Data Science - Basic,Technology->AI-Generative AI->Artificial Intelligence - BASIC\nEducation\nMaster Of Comp. Applications,Master Of Engineering,Master Of Science,Master Of Technology,Bachelor Of Comp. 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