You will get LLM | ML model deployment ready to integrate in Backends, Automations etc.
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Project details
Support variety of the models like: GGUF, ONNX, PH or PTH and even the LLM Models hostingSupport various AWS C loud Hosting service: AWS Sagemake, Sagemaker serverless, AWS Lambda, AWS ECS
Supported Type: GPU and CPU both
Experience in a variety of combinations from above everything listed. 100% guaranteed to get the custom tailored solution. All the solutions implemented by me are scalable and reliable; you get the best reliability for the least cost.
Supported Type: GPU and CPU both
Experience in a variety of combinations from above everything listed. 100% guaranteed to get the custom tailored solution. All the solutions implemented by me are scalable and reliable; you get the best reliability for the least cost.
Machine Learning Tools
Amazon SageMaker, ChatGPT, Python, SciPy, TensorFlowWhat's included $499
These options are included with the project scope.
$499
- Delivery Time 3 days
- Number of Revisions 0
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 1
- Model Validation/Testing
- Model Documentation
Optional add-ons
You can add these on the next page.
Fast 1 Day Delivery
+$50
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SP
Sh P.
Aug 15, 2025
Integrates Google Drive with AWS Textract (via Lambda or API Gateway)
I recommend working with Raj, good attitude, stuck with it until the end. He delivered a solid application at a fair price.
AK
Arjun K.
Jul 14, 2025
AWS Lambda
good work
SB
Shaked B.
Jul 8, 2025
Code bugs
He helped us very efficiently and effectively fix the memory leak and the retirement issues we had on the SaaS product at the startup, worked efficiently, effectively and to the point. Highly recommended
AM
Abstrak M.
Jun 1, 2025
DevOps Help Required
BW
Beod W.
Jan 22, 2025
AWS Custom Domain deployment
About Raj
Senior AWS, GCP and Azure Cloud Expert | Backend Engineer | DevOps
100%
Job Success
Surat, India - 10:41 am local time
I also specialize in AWS SageMaker, where I design, train, and deploy custom machine learning models as part of robust AI pipelines. Beyond that, I deploy AI-driven workflows with LangGraph, OpenAI APIs, and vector databases such as FAISS or Pinecone, ensuring seamless integration with cloud-native infrastructure. My work often involves deploying LLM-powered applications and autonomous agents to AWS using CI/CD pipelines, Docker, and Terraform.
I’m comfortable designing serverless and container-based pipelines with Lambda, ECS, and S3, and automating backend logic using Python frameworks like FastAPI and Flask. My approach balances performance, cost efficiency, and reliability, with attention to security, monitoring, and IAM best practices.
Steps for completing your project
After purchasing the project, send requirements so Raj can start the project.
Delivery time starts when Raj receives requirements from you.
Raj works on your project following the steps below.
Revisions may occur after the delivery date.
Get the requirments
Make a plan