Open to opportunities

Andrew Abdullah

@andrewabdullah

Message

Senior AI/ML engineer specializing in GenAI, LLMs, NLP, and production MLOps.

United States

Message

What I'm looking for

I’m looking to build and scale production-grade GenAI/LLM and NLP systems—owning end-to-end model development through MLOps on AWS/GCP/Azure, optimizing latency and reliability, and partnering cross-functionally to ship measurable improvements.

I’m an experienced AI/ML Engineer with 10+ years dedicated to designing and deploying intelligent systems using advanced machine learning and deep learning. I build robust pipelines, optimize models, and take AI solutions from prototype to production with a strong focus on performance and reliability.

At AssemblyAI, I led and mentored a team of 5 engineers while architecting production-grade ML models for speech-related use cases, including real time audio classification and fraud detection. I developed NLP pipelines using transformers like BERT and RoBERTa for sentiment analysis, intent detection, and voice-to-text understanding, applying A/B testing and experiment tracking to improve accuracy.

I’m hands-on with MLOps workflows and end-to-end deployment. I created and maintained systematized training pipelines using Airflow, MLflow, Docker, and Kubernetes, and integrated model monitoring and drift detection with Prometheus and custom Python scripts. I also collaborate cross-functionally to embed robust ML APIs into core product workflows.

Earlier roles strengthened my breadth across data engineering and model deployment, from scalable ETL pipelines for conversational analytics at Kore.ai to deep learning image classification and RESTful model inference APIs at DataRobots. I bring cloud-native experience with AWS SageMaker, GCP Vertex AI, and Azure ML, and I enjoy building scalable, reproducible ML systems that ship impact.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Engineer

Current

AssemblyAI

Jun 2023 - Present (3 years)

Led and mentored a team of 5 engineers, architecting and deploying production-grade ML models for real-time audio classification and fraud detection. Built NLP transformer pipelines and scalable training/CI-CD workflows using Airflow, MLflow, Docker, and Kubernetes, and improved performance with inference optimization plus Prometheus-based monitoring and drift detection.

NLP PyTorch Airflow MLFlow Docker Kubernetes Prometheus Model Monitoring

AI Engineer

Kore.ai

Nov 2019 - May 2023 (3 years 6 months)

Developed and maintained scalable ETL pipelines for chatbot conversational data using Python, SQL, and Apache Spark, improving intent classification accuracy with PCA/t-SNE/UMAP. Built automated dashboards and data validation checks, deployed anomaly detection to monitor chatbot responses, and implemented data labeling/annotation pipelines to accelerate supervised NLP model training.

ETL NLP Python SQL Apache Spark Dimensionality Reduction (PCA T SNE UMAP)Data Validation Anomaly Detection Data Labeling

Machine Learning Engineer

DataRobots

Apr 2016 - Oct 2019 (3 years 6 months)

Built and deployed deep learning pipelines for image classification using TensorFlow/Keras and PyTorch CNN architectures, ensuring optimized real-world performance. Developed RESTful inference APIs and production deployment with Docker and AWS ECS, and implemented Prometheus/Grafana model monitoring and drift detection; also contributed to AutoML for model selection and hyperparameter tuning.