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Build and deploy generative AI applications using LLMs and modern AI frameworks like TensorFlow or PyTorch.
Build embedded software and AI models for an autonomous tile-grouting robot using ROS2, C++, Python, and deep learning frameworks like PyTorch.
Build and deploy AI-powered software solutions, integrating ML models (PyTorch/TensorFlow) with full-stack development in Python and cloud platforms like Azure.
Designs and builds AI/ML models and agentic systems to automate workflows, enhance client engagement, and drive decision-making across retail, marketing, and operations using Python, LLMs, and cloud platforms.
Lead deployment and optimization of GenAI and Agentic AI pipelines, ensuring scalable, compliant operations through automation, monitoring, and governance across platforms.
Build and deploy AI/ML models for energy data at Halliburton, cleaning data, creating dictionaries, and serving models via APIs on cloud platforms.
Build and deploy AI/ML models for Singapore’s energy grid and regulatory needs, owning the full MLOps lifecycle from training to production monitoring and governance.
Build and deploy ML models and data pipelines using TensorFlow/PyTorch to power AI-driven software solutions.
Build and deploy AI models (computer vision, ML) and data pipelines to automate avionics workflows and deliver data-driven insights for Thales’ flight systems.
Build and scale the ML infrastructure powering ByteDance’s global ad, search, and e-commerce ranking systems using C/C++, CUDA, Python, and frameworks like TensorFlow/PyTorch.
Builds and owns large-scale data products handling petabytes of data, distributed systems, and ML pipelines to power advertising analytics and decision-making.
Lead AI initiatives for banking clients, designing GenAI chatbots and automation workflows using Microsoft AI tools and LLMs, while mentoring teams and aligning AI projects with business goals.
Build and deploy ML models in Python/TensorFlow/PyTorch to analyze large datasets, generate insights, and power real-time decisions for a Singapore-based AI product team.
Develops and optimizes a Python-based machine learning framework for search, ads, and recommendation systems using TensorFlow/PyTorch.
Backend engineering intern building scalable recommendation infrastructure using multi-modal content processing, vector retrieval, and RAG systems in Python/C++.
Design and implement Neo4j graph models for banking data, apply graph algorithms to detect fraud, and build real-time investigation dashboards for AML teams.
Build and optimize low-latency, high-throughput ML inference services for CTR/CVR prediction and generative recommendation using LLMs, focusing on GPU acceleration and end-to-end pipeline optimization.
Build and optimize high-performance ML kernels and compilation systems for recommendation/inference platforms powering apps like TikTok and Douyin.
Design and build scalable data pipelines on Databricks and cloud platforms, integrating diverse data sources to enable AI-driven analytics and business insights for enterprise clients.
Build and maintain data pipelines, warehouses, and ML models on Azure Databricks using Python, Spark, and TensorFlow to power analytics and predictions for a global logistics firm.
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