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2 months ago
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Requirements and responsibilities
What You’ll DoTranslate cutting-edge research into production-ready machine learning systemsDesign, build, and deploy end-to-end ML models and pipelinesDevelop and optimize models for image and video processingOwn the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deploymentBuild low-latency, real-time inference systems and scalable ML infrastructureRapidly prototype using open-source models and adapt them for product needsConduct experiments, analyze results, and iterate to improve performanceCollaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scaleStay current with advancements in machine learning and apply them to continuously improve productsWhat We’re Looking ForRequired QualificationsMS/PhD in Computer Science, Electrical Engineering, or related fieldStrong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS)5+ years of experience in Python and proficiency in Java, C++, or ScalaStrong understanding of multi-threading and memory managementSolid knowledge of ML architectures: CNNs, RNNs (LSTM/GRU), and TransformersExperience with PyTorch or TensorFlowExperience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applicationsExperience handling large-scale data using tools like SparkExperience deploying ML models in cloud environments (AWS preferred)Experience with experiment tracking systems and ML workflowsNice to HaveExperience in low level optimisation, cuda etc.Experience productionizing and scaling ML models in real-world systemsContributions to open-source projectsExperience with MLOps tools or distributed training systemsFamiliarity with relational databases (Postgres/MySQL)
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