{"id":3926958,"url":"https://alion.io/job/eigenstate-ai-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":4524406,"name":"eigenstate ai","domain":"eigenstateai.com","url":"https://alion.io/company/eigenstate-ai","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":"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":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CLIP","optional":false},{"name":"CNN","optional":false},{"name":"Computer Vision","optional":false},{"name":"EfficientNet","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Localization","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OpenCV","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"ResNet","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"YOLO","optional":false},{"name":"CUDA","optional":true},{"name":"Docker","optional":true},{"name":"ONNX","optional":true},{"name":"Synthetic Data","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-11-07T17:23:50Z","employer_posted_date":null,"last_verified_at":"2026-11-07T17:23:50Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"About the Company Eigenstate AI is looking for a Senior AI Engineer with strong hands-on experience in computer vision and deep learning.\nThe role involves designing, developing, optimizing and deploying AI solutions for real-world applications. We are looking for someone who can take ownership of end-to-end AI development, from problem-solving and model development to evaluation, optimization and production deployment.\n\nKey ResponsibilitiesDesign, develop and deploy computer vision systems for image and video-based applications.\nBuild solutions involving object detection, classification, segmentation, tracking and visual understanding.\nDevelop and optimise models using architectures such as CNNs (ResNet, EfficientNet), Vision Transformers (ViT, Swin, DeiT) and detection/segmentation models (YOLO, DETR, Mask R-CNN).\nImplement multi-object tracking algorithms such as SORT, DeepSORT and ByteTrack.\nDevelop video understanding and temporal reasoning capabilities using RNNs, Transformers and other relevant approaches.\nExplore multimodal AI systems combining vision and language using models such as CLIP, BLIP and similar architectures.\nApply classical computer vision and geometric techniques, including camera calibration, pose estimation, feature matching and depth estimation.\nTrain, fine-tune, evaluate and optimise deep learning models for accuracy, latency and scalability.\nBuild data pipelines for dataset curation, annotation, augmentation and model training.\nDeploy and integrate AI models into production environments, including GPU-based and edge infrastructure.\nResearch and experiment with emerging AI techniques to solve complex technical challenges.\nRequired Skills & Experience4+ years of hands-on experience in computer vision and applied deep learning.\nStrong programming skills in Python.\nProficiency in PyTorch or TensorFlow.\nPractical experience with object detection, segmentation and tracking systems.\nExperience with model training, fine-tuning, evaluation and optimisation.\nStrong understanding of representation learning, loss functions and deep learning fundamentals.\nGood understanding of evaluation metrics such as mAP, IoU, precision, recall and F1-score.\nExperience with image and video processing using OpenCV or similar frameworks.\nExperience building and deploying end-to-end AI solutions in production environments.\nUnderstanding of inference optimisation, GPU acceleration and scalable deployment.\nGood to HaveExperience with multimodal models such as CLIP, BLIP or similar Vision-Language Models.\nKnowledge of action recognition, video understanding and temporal modelling.\nExperience with human pose estimation, skeletal tracking and 3D vision.\nFamiliarity with NeRFs, SLAM, point clouds and depth estimation.\nExperience with ONNX, TensorRT, CUDA and model quantisation.\nKnowledge of active learning, hard-negative mining and synthetic data generation.\nExperience with distributed training and large-scale data pipelines.\nFamiliarity with Docker, cloud infrastructure and edge deployment.\nWhat We Are Looking ForStrong practical experience building and deploying AI solutions, beyond academic projects and experimentation.\nAbility to independently approach complex computer vision problems and identify suitable technical solutions.\nStrong understanding of the complete model development lifecycle.\nAbility to translate research and experimentation into reliable, production-ready systems.\nStrong ownership, problem-solving skills and collaboration with cross-functional engineering teams.\nCandidates whose experience is limited to academic projects or model experimentation without practical implementation and deployment experience may not be suitable for this role.","description_format":"text","description_chars":3718,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-11-07T20:10:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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