AI/ML Engineer
Kumail
Syed

Building end to end AI pipelines with Python, TensorFlow, PyTorch, and Scikit‑Learn containerized in Docker and orchestrated with Kubernetes.

  • Live in Lombard, IL
  • Experience 5+ Years
  • Date of Birth 26 May 1995
About Me
23
Completed
Project
65
Happy
Clients
14
Awards
Won

Hi, I’m Kumail Syed.
with over five years of experience architecting and deploying scalable AI/ML solutions in healthcare, finance, and e-commerce domains. Expert in end to end MLOps (Docker, Kubernetes, Jenkins, CI/CD), real time streaming analytics (Kafka, spark), and NLP/vision pipelines (BERT, ResNet).

Contact Me
My Resume

Senior Machine Learning Engineer with over five years of experience architecting and deploying scalable AI/ML solutions in healthcare, finance, and e-commerce domains. Expert in end to end MLOps (Docker, Kubernetes, Jenkins, CI/CD), real time streaming analytics (Kafka, spark), and NLP/vision pipelines (BERT, ResNet). Proven track record reducing model training time by 40%, cutting fraud-detection latency by 60%, and improving predictive maintenance accuracy by 25%.

SKILLS
Python
90%
MLflow
85%
PyTorch
80%
TensorFlow
95%
RESTful APIs
85%
SERVICES
AWS

Modern and mobile-ready website that will help you reach all of your marketing.

Python

Music copying, writing, creating, transcription and composition services.

RESTful

Advertising services include television, radio, print, mail, and web apps.

TensorFlow

Developing memorable and unique mobile android, ios and video games.

EDUCATION
2020
MicroMasters in Statistics and Data Science
Mitx
2019
Bachelor of Science (Computer & Information Science)
Lewis University
AWARDS
Amazon Web Services (AWS)
AWS Certified Machine Learning
Google Cloud
Google Cloud Professional Machine Learning Engineer
Docker, Inc
Docker Certified Associate
DeepLearning.AI Coursera
Deep Learning Specialization
Udacity
Machine Learning Engineer Nanodegree
EXPERIENCE
2023 - Present
UIS Technology Partners
Senior AI/ML Engineer
2021 - 2023
TEKsystems
ML Engineer
2019 - 2021
Apex Systems
Junior ML Engineer
My Projects

IT Infrastructure for Homeless Shelter

A mid market client’s IT support center struggled with slow ticket resolution due to manual triage and routing. UIS Technology Partners implemented an AI driven ticket classification system to streamline support operations. The solution leveraged Natural Language Processing (NLP) to automatically categorize incoming IT support tickets by issue type, urgency, and department, allowing faster assignment to the right teams. This initiative modernized the client’s helpdesk with intelligent automation, improving response times and consistency in support.

Enterprise MLOps & Data Science Hub

TEKsystems partnered with a global talent solutions company (Allegis Group) to accelerate enterprise wide adoption of AI and Machine Learning by building a centralized MLOps and Data Science Hub. The project involved designing a hub and spoke architecture that could serve multiple business units, enabling data scientists to deploy and scale ML models more efficiently. Over an intensive 8 week engagement, the team delivered a production ready MLOps pipeline that standardized how AI/ML models move from prototype to deployment. This initiative exemplified leveraging cutting edge cloud AI services to transform a traditional organization into an AI enabled enterprise.

Provider Matching NLP Engine

Apex Systems engaged with a health insurance provider to solve a data quality and efficiency problem using machine learning. The client’s operations involved matching lists of healthcare providers utilized by corporate policyholders against the insurer’s own provider network records. This process was previously done manually by a team and was extremely time consuming and error prone, due to inconsistencies in how provider names and addresses appeared across different data sources. Apex developed an AI powered provider matching solution that uses Natural Language Processing (NLP) and machine learning to automatically compare and reconcile provider information across multiple unstructured data sources. The result was a drastic reduction in manual effort (saving thousands of man hours) and improved accuracy in the network confirmation process.

Contact Me
+1 217 461 8437
kumailhsyed74@gmail.com
Lombard, IL