I will build and optimize mlops pipelines and deployment workflows
Senior Data and AI Engineer, AWS, Python, MLOps
Level 2
Has met high performance criteria and has a proven track record for meeting client expectations.
About this Gig
I help businesses build reliable and scalable MLOps solutions for deploying machine learning models in AWS and cloud environments. I specialize in Docker, Kubernetes, Jenkins, Airflow, CI/CD, APIs, and ML workflows to support cloud deployment, automation, orchestration, monitoring, and production readiness. I can help with deployment strategy, pipeline design, workflow automation, integration, and operational improvements for ML systems. My goal is to deliver efficient, maintainable, and business-focused MLOps solutions that improve reliability, scalability, and long-term performance through clear communication and strong technical quality.
Programming language:
Python
•
R
•
SQL
•
MLflow
•
Amazon SageMaker
Frameworks:
Scikit-learn
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Google ML Kit
•
Keras
•
PyTorch
•
Panda
FAQ
What do you need from me to get started?
Please share your project goals, current ML workflow, deployment environment, tech stack, and any existing architecture or documentation.
Which technologies do you work with?
I work with Python, AWS, Docker, Kubernetes, Jenkins, Airflow, APIs, CI/CD pipelines, and cloud-based ML workflows.
Can you help deploy models to the cloud?
Yes, I can help with deployment planning, cloud architecture guidance, automation workflows, monitoring strategy, and API integration.
Should I contact you before ordering?
Yes, especially for complex or custom projects. This helps ensure the package fits your exact needs.
