I

Iqbal Hafeez

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Ohio, United States

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work
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Résumé

Jobs verified_user 0% verified
  • N
    Senior AI/ML Engineer
    Nimer Tech
    Aug 2022 - Current (4 years 3 months)
    • Owned the end-to-end ML lifecycle for global predictive services by designing
    scalable architectures with PyTorch and AWS SageMaker.
    • Built an automated MLOps framework using MLflow that streamlined the model
    promotion process, successfully bridging the gap between R&D experimentation and
    production deployment.
    • Developed a high performance RAG pipeline using Pinecone and LLMs, which
    directly increased the accuracy of domain specific AI responses for complex user
    queries.
    • Optimized large scale transformer models for real-time use by implementing
    TensorRT and model quantization, significantly reducing inference latency.
    • Scales model training to billion parameter levels by designing di
  • Weights & Biases
    Senior ML Engineer
    Weights & Biases
    May 2020 - Jul 2022 (2 years 3 months)
    • Architected automated data ingestion and augmentation pipelines that increased
    model robustness across diverse, large-scale datasets.
    • Executed end-to-end model development for computer vision and regression tasks,
    including baseline training, hyperparameter tuning, and rigorous cross-validation.
    • Developed internal performance tracking dashboards using Flask and Streamlit,
    providing the data visualization necessary for informed, data driven decision
    making.
    • Standardized model lifecycle management by implementing version control for
    artifacts and experimental logs using Docker for containerization.
    • Optimized large-scale data workflows by refactoring SQL-based feature extraction
    queri
  • DataRobot
    Machine Learning Engineer
    DataRobot
    Feb 2018 - Apr 2020 (2 years 3 months)
    • Productionalized ensemble-based anomaly detection systems for real-time industrial
    monitoring, ensuring high availability and reliability for mission-critical
    applications.
    • Scaled feature engineering and data processing workflows using Spark, enabling the
    efficient handling of terabyte-scale datasets for deep learning training cycles.
    • NLP microservices using BERT and spaCy within a high-availability Kubernetes
    environment to deliver scalable, language-based intelligence services.
    • Automated the transition from experimental notebooks to modular production
    codebases, implementing full CI/CD integration and automated hyperparameter
    sweeping to accelerate development throughput.
Education verified_user 0% verified
  • B
    Bachelor in Computer Science
Projects (professional or personal) verified_user 0% verified
  • D
    Distributed MLOps Platform for Vision-Language Models
    • Engineered a distributed training engine to fine-tune multi-modal models across decentralized teams, featuring
    a continuous evaluation system that triggers automated rollbacks if performance drifts.
    Tech Stack: Ray, PyTorch FSDP, Tecton, Feast, DVC, and KL-Divergence monitoring
  • H
    High-Throughput Generative AI Gateway & RAG Orchestrator
    • Built a production grade inference gateway that serves Large Language Models with sub-100ms latency by
    integrating custom caching and request-batching logic.
    Tech Stack: FastAPI, Pinecone, LangChain, and Model Quantization (AWQ/GPTQ).