Machine Learning Engineer
3 weeks ago
Our mission is to transform the world by creating adaptive AI systems that empower innovation, enhance safety, and redefine connectivity for a smarter, more sustainable future.We are building scalable AI-driven solutions to power next-generation visual intelligence systems.
Join our team of passionate engineers and researchers to solve real-world computer vision problems across domains like robotics, smart cities, manufacturing, surveillance, and public safety - all while contributing to the future of embodied AI.Key ResponsibilitiesDesign, develop, and deploy robust computer vision models for object detection, classification, segmentation, pose estimation, tracking, and OCR tasksHandle end-to-end data management, including dataset curation, preprocessing, augmentation, and annotation for large-scale image and video dataImplement optimization techniques such as model quantization, pruning, and knowledge distillation for efficient edge deploymentOptimize model inference performance on both cloud and edge computing platformsDevelop and fine-tune deep learning architectures using modern frameworksIntegrate computer vision models into production pipelines and edge-based inference systemsCollaborate with MLOps/Dev Ops and product teams to deploy CV solutions at scaleResearch and evaluate emerging techniques to continuously improve system accuracy and efficiencyRequired Skills2+ years of hands-on experience in computer vision and deep learning developmentProficiency in Python with computer vision libraries and data processing toolsStrong expertise in deep learning frameworks for training custom models and leveraging pretrained architecturesExperience with deployment and optimization on edge computing devicesFamiliarity with hardware acceleration and model optimization toolsUnderstanding of classical computer vision techniques, including image processing fundamentalsExperience in data pipeline management for vision applicationsProficiency with version control systems and collaborative development workflowsBasic experience working with video streams from cameras, drones, or embedded platformsNice-to-HaveExperience with model serving frameworks and inference optimization toolsFamiliarity with MLOps practices and CI/CD pipeline integrationKnowledge of Vision-Language Models (VLMs) and multimodal AI systems for advanced visual understandingKnowledge of cloud AI services and edge computing platformsExperience with real-time object tracking algorithmsDomain experience in smart surveillance, OCR, safety detection, or embedded CV applications
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