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Design, build, and optimize ML models using Python or Java and frameworks like TensorFlow or PyTorch to solve complex problems from large datasets.
Develop and deploy deep learning models, handling data prep, training, and integration into systems while collaborating with cross-functional teams.
Build and maintain scalable AI infrastructure using MLOps, Kubernetes, and cloud-native pipelines to automate model lifecycle management for data scientists.
Build and deploy ML models for a multimodal AI platform using LLMs, RAG, and computer vision to enhance auto-tagging, OCR, and content analysis for enterprise clients.
Review AI-generated SQL queries and database designs, optimize performance, and ensure data quality for AI training solutions.
Red-team conversational AI models to uncover vulnerabilities, document findings, and improve safety and robustness of AI systems.
Builds and evaluates datasets for AI code models by writing and curating C/C++, Python, JavaScript/ReactJS, Java, Rust, and Go solutions.
Develops and implements AI/deep-learning models for computer vision and NLP, trains them on large datasets, and integrates solutions with cross-functional teams using Python and frameworks like TensorFlow or PyTorch.
Designs and builds AI/ML proof-of-concept prototypes and cloud-native solutions to validate business opportunities and drive digital transformation.
Architects QA strategy for an AI-driven IDP platform, leading end-to-end validation of OCR, LLM extraction, and cloud components while building scalable automation and mentoring the team.
Builds AI-powered chatbots and agentic systems using Python, FastAPI, LangGraph, and OpenAI SDK, integrating LLMs with workflow automation and deploying on AWS.
Build and fine-tune LLMs and RAG systems using TensorFlow, PyTorch, and LangChain, while maintaining scalable ML pipelines in cloud environments like AWS or Azure.
Build and maintain AI-driven recruitment tools like agentic workflows, RAG pipelines, and multi-model orchestration to automate hiring tasks and improve recruiter efficiency.
Design and build autonomous AI agents that decompose goals into actionable steps, integrate with enterprise systems, and deploy robust RAG pipelines with monitoring and governance.
Designs and delivers AI-native solutions using LLMs, agents, and MCP connectors, translating business needs into scalable, production-grade AI architectures.
Lead the design and deployment of AI-driven time-series forecasting models for financial risk, FX exposure, and treasury planning using Python, ARIMA, XGBoost, and Prophet.
Principal Data Scientist at i2c Inc leading fraud detection and AI systems, including transaction fraud, RAG chatbots, and agentic digital-CSR, while managing a team of ~20 data scientists.
Builds, deploys, and optimizes AI/ML models and pipelines for enterprise products, integrating GenAI, NLP, and predictive analytics into scalable systems.
Own AI-powered features for Pakistan’s largest auto marketplace, from discovery to launch, using LLMs and agentic workflows to automate buying/selling tasks and improve user outcomes.
Owns AI-driven product vision, roadmaps, and backlog; partners with engineers and data scientists to deliver AI-powered solutions using Agile practices.
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