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Lead AI/ML strategy and teams at early-stage startups, defining product roadmaps and deploying generative AI systems using Python, PyTorch, and cloud MLOps stacks.
Build and adapt AI models for early-stage startups, turning research into production systems and improving model performance, reasoning, and efficiency.
Principal AI/ML Engineer to architect and deploy cutting-edge models (LLMs, transformers) and lead AI strategy at high-growth startups in SignalFire’s portfolio.
Build and fine-tune deep-learning models (PyTorch, LLMs) to power a large-scale recommendation platform serving millions of users across finance, retail, media and healthcare.
Build and fine-tune deep-learning recommendation models in PyTorch to personalize offers across banking, e-commerce, media and healthcare for millions of users.
Build open-source AI solution blueprints and reference implementations for enterprise customers, focusing on production-grade architectures, MLOps, and secure deployments in regulated environments.
Builds and deploys predictive models and analytics to support financial data products and services at a global market-intelligence provider.
Research Scientist at NTU’s Alibaba-NTU Global e-Sustainability CorpLab, developing AI-driven sustainability metrics and vector-search systems to quantify ESG performance and reduce carbon footprints.
Builds and deploys AI/Generative AI solutions (LLMs, RAG, agentic systems) to optimize Mastercard’s pricing and interchange strategies, improving decision-making and operational efficiency in fintech.
Build and deploy generative-AI solutions using LLMs, prompt engineering, fine-tuning, embeddings, and RAG pipelines for enterprise use cases like customer service and document automation.
Build and lead AI-powered engineering solutions for a large bank, focusing on Gen AI tools like RAGs and agentic systems to improve software development workflows.
Lead AI/ML model development for banking use cases like fraud detection and document understanding using Python, LLMs, and cloud platforms.
Position Overview The AI Technical Architect is responsible for designing, developing, and implementing advanced artificial intelligence solutions that address critical business challenges. The role demands a deep…
Build and deploy end-to-end ML and Generative AI solutions for enterprise-scale problems in commercial operations, supply chain, and customer experience using Python, TensorFlow/PyTorch, and LLM frameworks like LangChain.
Lead AI integration at a global bank, building LLM-powered features and GenAI agents to enhance financial applications and user workflows.
Build and own full-stack AI applications for Amgen’s AI Studio, integrating LLMs, RAG, and automation into production systems using modern JavaScript/TypeScript, Python, and cloud services.
Build and own production ML/AI components for Amgen’s AI Studio, including GenAI, RAG, and retrieval systems, using Python, SQL, and cloud services.
Build and deploy production ML and GenAI components—models, RAG systems, agents, and pipelines—using Python, SQL, and cloud services to power Amgen’s healthcare-focused AI products.
Build and own full-stack AI-enabled applications for Amgen’s AI Studio, integrating LLMs, RAG, and automation into production healthcare systems using modern web and cloud technologies.
Build, train, and deploy AI models (ML, DL, generative, RAG, agents, computer vision) in Python, then wrap them in APIs for production use.
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