Shoaib Aktar · ML Engineer · 4+ yrs
Mid-LevelAbout Shoaib
Shoaib Aktar specializes in MLOps, focusing on the end-to-end lifecycle management of machine learning models. He has proven experience in deploying ML solutions using cloud platforms like Azure and AWS. His expertise includes building robust MLOps pipelines, implementing CI/CD flows, and ensuring the reliability and scalability of ML systems. Shoaib is adept at collaborating with cross-functional teams to drive projects from conception to deployment.
Core expertise
Additional skills(19)
TensorFlow
Jenkins
Git
SonarQube
GitHub
TerraformWhy hire Shoaib?
Designed and implemented robust MLOps pipelines across Azure Machine Learning and AWS SageMaker.
Automated infrastructure provisioning and configuration using Terraform and Ansible.
Streamlined the end-to-end lifecycle management of ML models by engineering and augmenting MLOps infrastructure.
Automated ML model deployment via CI/CD, ensuring reproducibility and efficiency.
Created robust monitoring and alerting infrastructures to safeguard model performance.
Project highlights(3)
MLOps Infrastructure Development – MLOps Engineer
Overview: Engineered, sustained, and augmented the MLOps infrastructure to streamline the end-to-end lifecycle management of ML models, from data acquisition and preprocessing to model training, validation, deployment, and monitoring. Responsibilities: Designed, developed, and implemented ML/LLM pipelines for AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring.
Key outcomes:
Streamlined end-to-end lifecycle management of ML models.
Ensured scalability, reliability, and security of operationalized ML systems.
Guaranteed consistent reproducibility and enhanced operational efficiency through automated pipelines.
Project 2 – MLOPS ENGINEER
MLOps Engineer — end-to-end ML lifecycle (data acquisition + preprocessing + training + validation + deployment + monitoring).
Key outcomes:
Streamlined end-to-end lifecycle management of ML models.
Ensured scalability, reliability, and security of operationalized ML systems.
Guaranteed consistent reproducibility and enhanced operational efficiency through automated pipelines.
Automated ML model deployment via CI/CD.
Project 3 – DEVOPS CoNsULtaNt
- Collaborated with development teams using Agile methodologies to actively contribute to the software development lifecycle (SDLC). Administered Linux/UNIX-based Operating Systems.
- Collaborated with development teams using Agile methodologies to contribute to the software development lifecycle (SDLC) actively.
- Administered Linux/UNIX-based Operating Systems and developed solutions using CI/CD tools such as Jenkins, Git, SonarQube, and Jfrog.
- Established standardized procedures for version control using Git or GitHub and automated infrastructure provisioning and configuration with Terraform and Ansible.
Key outcomes:
Developed CI/CD solutions to enhance the software development lifecycle.
Established standardized version control procedures using Git and GitHub.
Automated infrastructure provisioning and configuration, improving efficiency.
4+ years of industry experience
- •MLOps Infrastructure Development— MLOps EngineerPython · Azure Machine Learning · AWS SageMaker · Kubeflow +6
- •Project— MLOPS ENGINEERPython · Azure Machine Learning · AWS SageMaker · Kubeflow +6
At a Glance
Single contract. Billed in USD.
Typically responds within 4 business hours.
Top Skills
Vetted by WitaristNot sure if this is the right fit?
Tell us your requirements and we'll match you with the best candidates.
Shoaib Aktar
MLOPS Engineer