Saqib Farooq

Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying scalable machine learning, LLM, and MLOps solutions across enterprise environments. Adept at solving complex business problems with end-to-end AI systems from data ingestion and feature engineering to model development, deployment, and monitoring. Strong expertise in LLMs, generative AI, RAG architectures, and vector search, with hands-on experience integrating GPT-4, Claude, and LLaMA models into production workflows. Proven track record of architecting robust ML platforms using MLflow, Kubeflow, Kubernetes, and CI/CD pipelines, enabling automated model lifecycle management and reliable large-scale inference. Skilled in cloud-native development across AWS, GCP, and Azure, including distributed training, model optimization, and cost-efficient compute orchestration. Known for bridging engineering, data, and product teams translating business requirements into technical ML roadmaps, leading cross-functional initiatives, and delivering AI systems that enhance decision-making, accelerate operational efficiency, and drive measurable results. Passionate about building practical AI systems, improving model reliability, and pushing innovation in LLM-driven applications.