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Ishan Gupta

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4+ years of experience in: - Building and shipping production-grade Artificial Intelligence models - Provisioning petabyte scale MLOps (training) infrastructure on K8s - Setting up and deploying end-to-end data and model pipelines - Maintaining and optimizing the pipelines for cost efficiency and scale - Applying cloud-agnostic data engineering (ETL) with data jobs - Building and repurposing resilient and fault-tolerant distributed systems - Designing and developing horizontally scalable & H/A backends based on Micro-services architecture, powering robust web APIs I am interested in solving problems that require: - R&D on foundational AI models - Highly efficient and performant implementation of research papers and state-of-the-art models. - Novel approach to various aspects of AI and cloud - Training and fine-tuning large models (vision/language) on AI chips (GPU/TPU) and servers (DGX, HPE) - Concurrent or parallel computing with data processing - Batch and distributed systems for computing and storage - Building libraries for deep learning frameworks to enable generative AI use cases - Data from live streams and warehouses - Decentralized event-driven systems & H/A web-scale backend - Running application workloads on K8s My background: - I have worked on SaaS and OnPrem products at multiple early-stage startups, midsize firms, unicorns, and enterprises targeting B2B, B2C, and D2C markets. - Led multiple cross-geo and cross-team engineering initiatives at VMware by Broadcom. - Authored numerous HLDs and LLDs for systems architecture; iterated with feedback, reverse engineering, and innovation. - Contributor to multiple CNCF OSS projects. - Pursuing advanced degree in computer science and artificial intelligence with extensive research experience backed by several publications and post-graduate level coursework on mathematics for AI. - Udacity, Coursera, MITx, edX specializations, and certificates in Data Science, Machine Learning, Deep Learning, Reinforcement Learning, CUDA and JAX programming, Generative Artificial Intelligence, Quantum Computing, and Quantum Machine Learning - Cross-domain internships and projects include research-based applications of: * Natural Language Processing for chatbots * Computer Vision for game development and self-driving * On-device ML for mobile app development * Data Science for GIS * Chaos Engineering for SRE * Languages: Golang, Scala, Python, R, Java * Frameworks/libraries: controller-runtime, Beam, Pyspark, PyTorch, Keras (Tensorflow), Ray, Kubeflow, LangChain, autogen, OpenCL, NLTK, OpenCV, Django, Spring

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