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Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed…
Build and maintain AI infrastructure and cloud environments for government AI projects, including MLOps pipelines, model serving, and security protocols.
Build and scale ML training and inference infrastructure for autonomous robots, focusing on data pipelines, distributed training, and GPU optimization.
Brief Summary: Join our dynamic team as we innovate in AI solution development, focusing on Generative and Agentic AI technologies. We are seeking a skilled professional to drive the design and implementation of AI…
Lead the design and deployment of production-grade ML/AI systems using Azure ML, Databricks, and PySpark, ensuring scalable, reproducible, and monitored models in a CI/CD/CT pipeline.
Leads AI strategy for a global product company, designing and scaling recommendation systems, user search, and autonomous agentic models (LLMs, RAG, orchestration) to improve discovery and personalization at scale.
Lead the 0-1 build of an AI-native data infrastructure platform, defining architecture, hiring the team, and shipping production-grade ML/GenAI systems that power core platform capabilities.
Designs, trains, and deploys machine learning models in production, optimizing pipelines and collaborating with engineering teams to integrate AI solutions at scale.
Build and deploy AI/ML systems to solve engineering and construction challenges for high-tech facilities using Python, C++, and frameworks like PyTorch or TensorFlow.
Designs, trains, and deploys machine-learning models and pipelines, optimizing performance and integrating them into production systems using Python, PyTorch, and cloud platforms.
Design and optimize AI models (RAG, Agentic AI) using Python and frameworks like TensorFlow/PyTorch, and deploy them on cloud platforms.
Builds and evangelizes LaunchDarkly's AI agent control product, advising customers, shaping product feedback, and creating technical content to drive adoption of multi-agent systems.
Build and deploy ML/AI systems in Python using libraries like TensorFlow and PyTorch; develop scalable AI solutions for real-world applications.
Build quantitative models and ML pipelines to power equity research, turning financial data into research-grade signals and insights for analysts and clients.
Build and deploy AI/computer-vision systems end-to-end, from data pipelines and model training to C++ edge integration and production validation.
Build and validate statistical and machine-learning models in Python/R to extract insights from large datasets and support data-driven decisions for clients.
Build and deploy ML models in Azure to extract insights and drive decisions using Python and cloud data tools.
Build and deploy AI models and data pipelines for a product company, focusing on deep learning and data science.
Build and optimize cloud-based SQL databases and data pipelines in Azure, then collaborate with data scientists to develop Python-based ML models for analytics across fintech and healthcare.
Build and deploy AI-powered SaaS that integrates ML models and analytics into daily decision-making using Python, Node.js, and cloud-native tooling.
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