Syed Attiq

SA

Open to opportunities

Syed Attiq

@syedattiq

I build production AI platforms spanning LLMs, RAG, computer vision, and real-time inference.

At Whatnot, I design and deliver enterprise-scale AI/ML systems across Generative AI, LLMs, NLP, computer vision, predictive modeling, and real-time AI. I build RAG and agentic AI pipelines, conversational copilots, customer-facing AI applications, and production APIs using Python, FastAPI, React, and TypeScript.

Previously at Prismetric and Magna International, I developed NLP, computer vision, predictive modeling, and distributed ML workflows. I bring end-to-end experience from data engineering and model development through AWS, Kubernetes, MLOps, monitoring, governance, and continuous improvement.

Experience

Work history, roles, and key accomplishments

WH

Current

Lead AI/ML Engineer

Current

Jan 2022 - Present (4 years 8 months)

Designed and delivered enterprise-scale, production-grade AI/ML solutions across Generative AI, LLMs, NLP, Computer Vision, predictive modeling, and real-time AI. Architected end-to-end ML workflows including data engineering, model development, deployment, and monitoring.

Generative AI LLM NLP Computer Vision PyTorch TensorFlow Hugging Face Transformers Lang Chain RAG Agentic AI fastAPI React TypeScript PostgreSQL AWS Docker Kubernetes Terraform MLFlow Kubeflow Airflow PySpark Databricks

PR

Senior AI/ML Engineer

Prismetric

Mar 2019 - Jul 2022 (3 years 4 months)

Developed production AI/ML solutions across Generative AI, NLP, conversational AI, computer vision, deep learning, and real-time inference. Built transformer-based NLP/LLM and RAG applications with contextual memory and AI agents.

PyTorch TensorFlow Hugging Face Transformers Lang Chain RAG Computer Vision OpenCV YOLO Faster RCNN SSD ResNet VGG EfficientNet TensorRT fastAPI AWS Docker Kubernetes MLFlow Airflow PySpark Databricks

MI

Machine Learning Engineer

Magna International

Aug 2015 - Feb 2019 (3 years 6 months)

Developed supervised and unsupervised ML solutions using Python, NumPy, Pandas, SQL, and scikit-learn for predictive modeling, classification, regression, and feature engineering. Built scalable ML and data workflows using PySpark, Apache Spark, and Databricks.

Python NumPy Pandas SQL scikit learn PySpark Apache Spark Databricks TensorFlow PyTorch OpenCV YOLO SSD ResNet VGG fastAPI PostgreSQL AWS REST APIs

Education

Degrees, certifications, and relevant coursework

FU

FUUAST University

Bachelor of Science

Bachelor of Science degree from FUUAST University.

Tech stack

Software and tools used professionally

Apache Spark

Kubernetes

NumPy

Pandas

PySpark

PostgreSQL

Databricks

OpenCV

Terraform

React

Python

TensorFlow

PyTorch

MLflow

scikit-learn

Kubeflow

FastAPI

AWS Lambda

TypeScript

Docker

Airflow

SQL

LangChain

BentoML

Availability

Open to opportunities

Location

United States

Authorized to work in

Job categories

Machine Learning Engineer AI Engineer MLOps Engineer Data Engineer Computer Vision Engineer

Skills

Machine Learning Supervised Learning Unsupervised Learning Semi Supervised Learning predictive modeling Classification regression Feature Engineering Model Training Model Evaluation scikit learn Cross Validation Hyperparameter Tuning Statistical Analysis Experimentation A B Testing Experiment Tracking AutoML Large Language Models Generative AI Transformer Architecture Prompt Engineering LLM Fine tuning Inference Optimization RAG NLP Conversational AI AI Agents Agent orchestration Tool calling Intent Detection Contextual Memory Multiturn Dialogues Hugging Face Transformers Lang Chain PyTorch TensorFlow CNN RNN LSTM OpenCV YOLO Faster RCNN SSD ResNet EfficientNet VGG Transfer Learning Image Classification Object Detection Image Segmentation TensorRT Real Time Computer Vision MLFlow Kubeflow Airflow AWS Sagemaker TensorFlow Serving BentoML Docker Kubernetes Databricks Model Versioning Monitoring Drift Detection Deployment Validation CI CD Continuous Integration Continuous Deployment Distributed Systems Cloud Native AI AWS AWS Lambda EC2 S3 Microservices REST APIs fastAPI API Development Distributed Inference Scalable ML Infrastructure Real Time AI Systems Terraform Infrastructure as Code Performance Optimization Reliability Observability PySpark Apache Spark SQL PostgreSQL NoSQL ETL ELT Data Pipelines Data Validation NumPy Pandas React TypeScript Python AI Copilots Agentic Applications graph neural networks Graph ML Reinforcement Learning Multi Agent Systems Bayesian Modeling Probabilistic Programming Anomaly Detection Responsible AI Ethical AI Model Governance Auditability AI Risk Assessment Risk Mitigation Bias Detection Fairness Regulatory Compliant AI

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