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I will deploy your ai or ml model on AWS sagemaker and automate predictions
Dilshad
Level 2
About this gig
Want to automate your ML/AI model workflow and get predictions without any manual work? I can help! I specialize in deploying models, feeding data, and storing outputs, making your ML pipelines seamless and efficient.
What I Can Do for You
- Deploy ML Models Work with pickle (.pkl) or binary/JSON models on AWS SageMaker
- Automate Data Flow Extract data from data warehouses or run SQL queries to feed your model automatically
- Store Predictions Save outputs to S3 buckets or directly load into tables
- Event-Based & Scheduled Runs Automate workflows on a specific time or triggered event
- Flexible Solutions Use Airflow + Papermill for smaller datasets; scale to SageMaker for larger workloads
- Proven Experience Already automated pipelines from Snowflake export data model predicted scores table/S3
Why Work With Me
- Expert in AWS SageMaker, Airflow, and Papermill
- Handle both small and large datasets efficiently
- Deploy .pkl and JSON binary ML models for predictions
- Build reliable, automated, production-ready ML pipelines
- Provide guidance and support to make sure your automation runs smoothly
Get to know Dilshad
Dilshad
Lead Data Engineer, 10 Years, Cloud Expert, Results Over Words
Level 2
- FromIndia
- Member sinceOct 2020
- Avg. response time1 hour
- Last delivery2 months
Languages
Punjabi, English, Hindi, Urdu
Lead Data Engineer, 10+ years enterprise experience. Expert: Snowflake, AWS, Airflow, Terraform, Hadoop, Hive, SQL. Led teams, architected platforms, achieved 40-60% cost reductions. Specializes: cloud migrations, pipeline optimization, infrastructure automation. Successfully delivered 100+ projects with zero downtime. Built data teams, established best practices. Philosophy: results over words. Focus: sustainable architecture, technical excellence, business value delivery. Proven leadership in complex system transformations.
FAQ
Can you provide guidance or support after deployment?
Of course! I provide ongoing support, monitoring, and guidance to ensure your automation runs smoothly and efficiently.
Have you done this before in real projects?
Yes! I have automated workflows where data was extracted from Snowflake, fed to models (.pkl and JSON binary), predictions were generated, and results stored in tables or S3.
Can you schedule the ML pipeline to run automatically?
Yes! I can set up time-based schedules or event-triggered pipelines so your models run automatically whenever needed.
Can you handle small and large datasets?
Absolutely! For smaller datasets, I use Airflow + Papermill. For larger datasets, I use AWS SageMaker to automate pipelines efficiently.
Where will the prediction results be stored?
Predictions can be stored in S3 buckets or loaded directly into database tables, depending on your workflow needs.
Can you automate data extraction from my database?
Yes! I can extract data from data warehouses or run SQL queries to feed your model automatically. The process can be scheduled or event-driven.
What types of ML models can you deploy?
I can deploy pickle (.pkl) files, binary/JSON models, and other ML/AI models on AWS SageMaker or via Airflow pipelines for automated predictions.
