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Designs, trains, and deploys AI models using Python and PyTorch/TensorFlow, integrating them into production systems with cloud deployment.
Staff Data Scientist at Mozn builds and deploys NLP models and AI strategies to extract insights from large datasets, collaborating with leadership and engineering to drive data-driven decisions.
Design and deploy AI/ML models (predictive, NLP, computer vision) for enterprise use cases, collaborating with stakeholders to deliver end-to-end analytics solutions on large-scale data.
Build and deploy production-grade AI/ML models and features, focusing on deep learning, MLOps, and end-to-end automation for measurable business impact.
Maintains and optimizes cloud and on-prem infrastructure for a healthcare-focused AI speech-recognition platform, using Kubernetes, Terraform, and CI/CD pipelines.
Build and maintain cloud and on-prem infrastructure for a healthcare-focused AI speech-recognition platform, using Kubernetes, Terraform, and CI/CD pipelines.
Data Scientist builds predictive models and dashboards in Python/R with Power BI, working with stakeholders to turn business needs into data-driven insights and solutions.
Build knowledge-graph and AI-driven analytics to detect fraud and risk patterns using Python, LLMs, and graph reasoning.
Build internal UX research tools using React/Angular front-end and Java/Python/Go back-end to help Google teams rapidly turn user insights into product decisions.
Build, deploy, and maintain ML models and data pipelines in Python/SQL, using scikit-learn, PyTorch/TensorFlow, and MLOps tools like MLflow to productionize insurance-focused solutions.
Build, deploy, and maintain ML models and data pipelines in Python/SQL, using scikit-learn, PyTorch/TensorFlow, and MLOps tools like MLflow to move prototypes into production.
Designs and builds scalable data pipelines, models, and integrations for AI/ML and reporting, translating business needs into technical solutions with minimal oversight.
Design and implement AI solutions for enterprise clients, integrating GenAI, NLP, and multimodal systems while optimizing algorithms and reducing latency.
Design and deploy AI solutions to optimize logistics workflows, using LLMs and GenAI tools to streamline project delivery and cross-functional coordination.
Develop and deploy AI/ML models for a retail bank, from PoCs to production, focusing on NLP, deep learning, and generative AI to solve business problems.
Build and improve AI-powered financial research tools using LLM, RAG, vector search, and agentic workflows for a market intelligence platform.
Build and optimize full-stack web and mobile platforms alongside AI-driven features like recommendations and chat interfaces using React/Next.js, Node.js, and LLM tools.
Builds a document IDE for non-engineers using C# and .NET, improving performance, synchronization, and NLP-powered features like federated learning.
Builds production-ready AI applications and agents for financial services, integrating LLMs and APIs into enterprise workflows while ensuring compliance and performance.
Builds AI-powered features and agent-based systems for financial services, integrating LLMs and APIs into production applications while ensuring compliance and performance.
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