Ahmad Hayes
@ahmadhayes1
I am a Senior Machine Learning Engineer specializing in Generative AI, LLMs, and production-ready AI systems.
What I'm looking for
I am a Senior Machine Learning Engineer and AI/ML architect with over a decade of experience building scalable, production-grade AI solutions focused on Generative AI, large language models, and NLP.
I have designed and deployed transformer-based systems (BERT, RoBERTa, GPT, T5) and built Retrieval-Augmented Generation pipelines integrated with vector databases such as FAISS and Pinecone. I’ve developed intelligent document understanding, OCR, and entity-extraction systems and optimized inference using Kineto trace, CUDA/Triton kernels, and operator-level profiling.
I lead MLOps and experimentation workflows—implementing MLflow and Weights & Biases for tracking, CI/CD for model packaging, containerized deployments with Docker and Kubernetes, and parameter-efficient fine-tuning (LoRA/PEFT). I’ve built FastAPI/TorchServe/Triton-backed microservices and production monitoring for latency and model quality.
I look to contribute to teams building high-impact GenAI products where I can drive architecture, performance optimization, and reliable, scalable deployment of LLM-powered applications.
Experience
Work history, roles, and key accomplishments
Senior Machine Learning Engineer
Klarity Labs
Jan 2021 - Present (4 years 7 months)
Designed and deployed end-to-end Generative AI systems using transformer LLMs for enterprise NLP use cases and built RAG pipelines with FAISS and Pinecone for real-time contextual search. Productionized ML APIs with FastAPI, Docker, and Kubernetes and profiled/optimized inference using Kineto trace and CUDA/Triton kernels.
Senior Machine Learning Engineer
CognitiveScale
Jul 2019 - Dec 2020 (1 year 5 months)
Led design and development of multilingual NLP systems for sentiment analysis, text classification, and information extraction, integrating BERT and XLNet to improve semantic understanding. Built ETL and model orchestration pipelines with Apache Airflow and Docker and deployed models via Flask and TensorFlow Serving.
Machine Learning Engineer
Mavericks United
Aug 2015 - Jun 2019 (3 years 10 months)
Developed multilingual NLP systems and information extraction pipelines using modern deep learning models and integrated pre-trained models like BERT to improve application accuracy. Implemented automated ETL workflows and model orchestration with Apache Airflow and Docker and deployed real-time predictions via Flask and TensorFlow Serving.
Education
Degrees, certifications, and relevant coursework
Preston University
Master of Science, Computer Science
Master of Science in Computer Science from Preston University.
Tech stack
Software and tools used professionally
Amazon Redshift
Azure Synapse
Apache Spark
Apache Flink
Superset
Bokeh
GitHub
GitLab
Bitbucket
Kubernetes
Jenkins
GitHub Actions
GitLab CI
Jupyter
NumPy
Pandas
PySpark
MySQL
PostgreSQL
MongoDB
Cassandra
Hadoop
InfluxDB
HBase
Gmail
Databricks
OpenCV
Redis
Terraform
Pulumi
Jira
Java
Julia
MATLAB
TensorFlow
PyTorch
MLflow
scikit-learn
Keras
Kubeflow
Neptune
NLTK
Kafka
FastAPI
Grafana
Prometheus
Serverless
Kafka Streams
Airflow
Apache Beam
Google BigQuery
TimescaleDB
CUDA
SQL
XGBoost
Hugging Face
LightGBM
CatBoost
Podman
Qdrant
LangChain
Weights & Biases
Evidently AI
BentoML
Pinecone
Tecton
Feast
Delta Lake
Great Expectations
Availability
Location
Authorized to work in
Job categories
Skills
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