AWS Deployment of Dual-Model

@gunslinger

This is really about structuring the pipeline correctly on AWS so the models run reliably under real usage, not just getting them to run once. I have worked on similar setups using SageMaker, API Gateway, and S3 flows, so I am comfortable handling the full process from DICOM upload with presigned URLs to running concurrent inference and returning structured outputs. I would make sure both models are properly containerized, the pipeline stays stable under load, and the endpoint is clean and secure. I can jump in quickly and get this deployed in a way that is solid and maintainable.

@Softeria

✅ Proposal for AWS Deployment of Dual With a strong background in AWS solutions and medical imaging pipelines, I am ideally suited to deploy your dual-model pipeline on AWS. My experience includes setting up secure, scalable AWS environments using SageMaker, Lambda, and API Gateway, tailored for high-load medical data processing. I have successfully implemented similar architectures, integrating complex models like Pillar-0 and Sybil-1.5 for predictive analytics. My technical proficiency extends to handling large datasets with the Locker Pattern and ensuring compliance with healthcare data standards. I am committed to delivering a robust, secure endpoint that meets your projects specific needs. Let’s connect to bring this critical tool to fruition.

@bindmission

Hello, I have 10 years of experience in cloud architecture and AWS deployments. I propose to deploy and integrate the dual-model pipeline on AWS SageMaker as per the project requirements. We will ensure that the models are hosted on appropriate GPU instances and implement the API Gateway and Lambda for efficient orchestration. The pipeline will handle zipped DICOM files for 3D reconstruction and concurrent inference using Pillar-0 and Sybil-1.5. The "Locker Pattern" with pre-signed URLs will be implemented for large file uploads to S3. We will configure the necessary AWS infrastructure, including custom domain management with SSL. The solution will deliver a secure and scalable AWS endpoint, complete with sample output data in JSON and PDF. Regards, VishnuLal NB*

@chraheelbhatti

As a seasoned PhD Researcher and Senior Machine Learning Engineer with over 10 years of experience, my expertise lies precisely in the domains required for your project. I have a strong background in Computer Vision, which is vital for deploying your dual-model AWS pipeline. Additionally, my extensive knowledge of deploying powerful ML models on AWS SageMaker ensures that I can adeptly handle the heavy-duty aspect of your task. Lastly, as a cloud enthusiast experienced in working with AWS services such as Lambda, API Gateway, and S3 Permissions, I am confident about managing AWS Cloud Architecture efficiently just like you require in your proposal. From developing a key maker function for handling large volumes to ensuring endpoint security and production readiness, no detail will go overlooked under my watch. Embracing a synergy of technical brilliance and rigorous project management that has delivered results for major institutions including Unilever and State Bank of Pakistan, I assure you an optimized AWS setup that not only deploys the dual-model pipeline proficiently but is scalable for future enhancements as well.

@FaizalShaik80

Hi, I would love to help. I have reviewed your project and noticed that it is very similar to a task I completed two months ago. I am a skilled freelancer with 6+ years of experience in Python, Machine Learning (ML), API Development and I can deliver the results as quickly as possible. You can visit my profile to check my latest work and recent reviews. Looking forward to working with you, connect in chat. Regards.

@MRARIFAKRAM

As an AWS and Python expert with 8 years of experience, I can confidently say, few projects are as well-suited to my skills as this one. I have deep knowledge not just of these two key areas but also in Linux system administration, software engineering which aligns closely with the landscape of technology you require for this project. I'm comfortable working across diverse environments and platforms from mobile applications to large-scale cloud deployment.

@ianb65

Hello, there! I can deploy this dual-model AWS pipeline end to end, including SageMaker GPU hosting, concurrent inference from zipped DICOM volumes, secure S3 upload flow with pre-signed URLs, and production-ready API delivery behind API Gateway and Lambda. My background includes building scalable cloud systems across AWS, optimizing backend performance, and delivering secure deployment pipelines with reliable automation and observability, which aligns well with the infrastructure and inference workflow you need. I can package the Atlas architecture and Sybil-1.5 exactly in the required SageMaker model structure, implement the locker-pattern upload flow for large CT volumes, wire S3 permissions and endpoint access correctly, and produce both radiology-style JSON and PDF outputs from test studies. I can also handle the custom domain, ACM, Route 53, and harden the stack for production use on g5.2xlarge instances. Best regards, Ian Brown

@emilesd617

Hi, I am a Python and AWS developer with 8 years of rich experience with a background in ML infrastructure and model deployment. I am familiar with Python, AWS SageMaker, Lambda, S3, API Gateway. For this project, the most important part is building a stable inference pipeline for large DICOM volumes with secure upload and GPU model execution. This ensures both models run correctly, large files are handled safely, and the API is production-ready. I will focus on SageMaker deployment, pre-signed S3 upload flow, concurrent inference, and clean JSON/PDF report output. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.

@durgesh8527

I specialize in building high-performing web and mobile applications, which perfectly aligns with the requirements of this project. With over 12 years as a full-stack developer and extensive experience in Python, I'm well-versed in developing solutions like the one you need for AWS Deployment of Dual-Model. Additionally, I have a sound understanding of AWS, having worked on multiple projects involving SageMaker, API Gateway, Lambda, and S3 permissions, among others. This makes me an ideal candidate to ensure smooth deployment and efficient operation of your dual-model pipeline on AWS. Finally, my knowledge extends beyond just the technical aspects. Having developed cloud-based applications, I understand the importance of maintaining data integrity and user privacy. Rest assured, I will build a secure and production-ready system capable of handling your large volumes while implementing the "Locker Pattern". Let us connect to discuss the project details further and get started immediately.

@mickeysz

Hello, I’m an AWS-focused ML engineer with strong experience in Python, SageMaker (GPU deployments), and medical imaging pipelines, including DICOM handling, 3D reconstruction, and multi-model inference. I’ve deployed similar architectures using SageMaker endpoints with custom inference scripts, integrated S3 pre-signed upload flows (“locker pattern”), and built API Gateway + Lambda front doors with secure, production-ready setups. Your dual-model pipeline (Pillar-0 + Sybil-1.5) and radiology-style output fits well with my background in concurrent inference, optimized GPU utilization, and structured report generation (JSON/PDF). Quick questions: do you want real-time synchronous inference via SageMaker endpoint, or async processing (SQS/SNS) for large volumes? Also, should the PDF report follow a specific clinical template (e.g., structured sections for findings/impression), and do you already have IAM/security policies defined for HIPAA-like compliance? I can handle full deployment (S3 structure, model packaging, endpoint, API, domain, SSL) and ensure stable, low-latency performance. I look forward to hearing from you. Best regards

@ArchnaAdmin

Hi, I have 8+ years of experience working with AWS cloud infrastructure and services, including EC2, S3, Lambda, IAM, RDS, CloudFront, Route 53, SES, SQS, SNS, CloudWatch, and API Gateway to build scalable, secure, and reliable environments. I handle server deployment, S3 storage setup, database management, email services with SES, security configuration, monitoring, performance optimization, and automation workflows. I also have experience with AWS migrations, including moving S3 buckets, EC2 instances, EBS volumes, and RDS databases between accounts or environments with minimal downtime and no data loss. Please share your requirements to proceed. Thank you

@DigitalLogics

Hi there, I can deploy this as a stable, production-ready dual-model pipeline on AWS, focused on reliable GPU inference and clean data flow. I’ll package Pillar-0 (Atlas) and Sybil-1.5 into a single SageMaker endpoint on g5.2xlarge, structured exactly to your required model layout so loading and execution stay predictable. The pipeline will take zipped DICOMs, handle 3D reconstruction, and run parallel inference efficiently without GPU or memory issues. For large uploads, I’ll implement the Locker pattern with a Lambda-based pre-signed URL system so clients can push 500MB files directly to S3 without hitting API limits. API Gateway will handle requests with proper zip support and return structured radiology-style JSON and PDF outputs. I’ll also configure IAM, S3 access, and custom domain with SSL so everything is secure and ready for real usage, not just testing. If you want this running smoothly without breaking under real data loads, I can get a working endpoint live quickly. Best; Zaman

@jeanpatrickr8

Hello, I appreciate the opportunity to bid on your project involving the deployment of a dual-model pipeline on AWS. I understand that you require a comprehensive solution that integrates both the Pillar-0 and Sybil-1.5 models for medical image analysis and lung cancer risk prediction. With extensive experience in AWS deployment and machine learning models, I have successfully implemented similar projects utilizing AWS SageMaker and Lambda functions. My expertise includes working with DICOM files, 3D volumetric reconstruction, and building secure API endpoints. To achieve your project goals, I propose the following approach: - Deploy the Pillar-0 and Sybil-1.5 models on AWS SageMaker using GPU instances for optimal performance. - Implement a Lambda function to generate pre-signed URLs for secure uploads of large DICOM files directly to S3. - Configure the API Gateway with proper binary media types and manage the networking stack, including custom domain setup and SSL/TLS certificates. - Ensure that the output meets your specifications by generating JSON and PDF reports from the inference results. I am excited about the possibility of collaborating on this project and confident in my ability to deliver high-quality results on time. I am available to discuss further details and can begin immediately. Thank you for considering my proposal.

@haseebsidd07

Hey , I just went through the project description, and I see you are looking for someone experienced in Python, Model Deployment, Deep Learning, Hugging Face, JSON, AWS SageMaker, API Development, Machine Learning (ML) and Amazon Web Services. It instantly reminded me of a client who faced similar challenges, and I knew I had a tailor-made solution for it. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: • Is there anything else you’d like to add to the project details? • What’s the top hurdle you’re facing with this project? • What is the timeline to get this done? Why Choose Me? 250+ Projects. 5 Years. Zero Misses. My reputation is built on a single metric: Flawless Execution. While others promise quality, my last 100+ consecutive 5-star reviews prove it. I don’t just finish the job; I set the standard. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) The portfolio here is just the tip of the iceberg. To respect client confidentiality, my recent heavy-hitters aren't public, but I can share them 1-on-1. Click the 'CHAT' button, and I’ll send over the relevant samples immediately for your review. Regards, Abdul Haseeb Siddiqui.

@atesicfl

⚡ I'm ready to start! ⚡ I’m an AWS focused engineer with experience deploying GPU backed ML pipelines on SageMaker, including medical imaging workflows with DICOM processing and secure API layers. I’ve built systems that handle large file ingestion, concurrent inference, and structured report generation with reliable performance in production. You’re aiming for a production ready dual model pipeline that processes large CT volumes, runs parallel inference, and returns consistent radiology style outputs through a secure API. I would package both models into a SageMaker endpoint on g5 instances, implement the Lambda driven pre signed upload flow with S3, and connect everything through API Gateway with proper auth, domain, and SSL setup while ensuring the inference pipeline handles 3D reconstruction and concurrency cleanly. I’ll keep the deployment structured, reproducible, and well tested so uploads, locking, inference, and reporting behave exactly as expected. I would be glad to work with you on this project. Thanks.

@ivicab6

With my skills and experience in full-stack engineering, including a deep understanding of Python and Machine Learning, I believe I'm a perfect fit for your AWS dual-model deployment project. Over the past 6+ years, I have successfully deployed numerous production web applications with a strong focus on clean architecture and performance optimization - qualities that will be vital in your project. As part of my deployments, I have also worked with data pipelines, analytics, and ML components - including platforms like Hugging Face. Your AWS deployment, involving the hosting of models on SageMaker and implementation of an API Gateway + Lambda front-door is within the scope of my expertise. Similarly, my proficiency in optimizing AWS cloud architectures to ensure the best is delivered while maintaining security aligns perfectly with your project goals. Moreover, I pride myself on my ability to tackle complex challenges head-on. The task of developing a Lambda-based "Key Maker" for handling large zip file uploads via pre-signed S3 URLs is one such challenge. I assure you that not only will I handle this task efficiently, but I will also ensure that the entire project is secure and production-ready. Let's work together to reduce manual work, eliminate operational errors and deliver an outstanding solution for your unique AI use case!

@jordanrafael7

Hello, I’ve reviewed your AWS deployment requirements for the dual-model medical imaging pipeline. I understand this involves GPU-based inference, DICOM processing, and a secure, production-ready architecture—not a simple deployment. I can build and deploy a scalable pipeline that handles large CT uploads, performs 3D reconstruction, and runs concurrent inference using Pillar-0 and Sybil-1.5. Approach: Package models (Atlas + Sybil) into SageMaker (ml.g5.2xlarge) with proper structure Implement inference pipeline for zipped DICOM → 3D volume → dual-model prediction Build API Gateway + Lambda entry point Implement S3 pre-signed URL (“Locker Pattern”) for large uploads Configure IAM roles, secure access, and S3 integration Set up custom domain (Route 53 + ACM SSL) Generate structured JSON + PDF radiology-style reports Deliverables: Live secured API endpoint Fully deployed SageMaker model with GPU support End-to-end pipeline from upload → inference → report Pre-signed upload system for large files Production-ready AWS architecture I’ve worked with AWS, ML model deployment, and data pipelines, ensuring reliability, performance, and secure handling of large datasets. Best regards, Jordan Rafael

@souravsasmal14

As a Full-Stack Developer and DevOps Engineer, I am well-versed in the deployment of complex systems like the one you require. Having mastered both Node.js and PHP stacks, my skills align perfectly with your need for deploying the AWS API Gateway and Lambda front-door. My experience extends to Linux administration, making me efficient in configuring the networking stack using ACM (SSL/TLS), API Gateway, and Route 53. Combining these with my proficiency in Python and familiarity with GPU instances on AWS like ml.g5.2xlarge, I can flawlessly put your dual-model on SageMaker for significant computational power. Furthermore, I possess mastery over API development coupled with expertise in Machine Learning (ML). Such a combination of skills provides me with the capacity to comprehend the 'Locker Pattern' unique to multi-findings across Chest, Abdomen, Brain, and specialized future lung cancer risk prediction. I can develop a Lambda-based "Key Maker" for your 'Pre-signed S3 URL workflow' that will seamlessly handle upload links up to 500MB. In conclusion, my extensive experience in deploying large-scale applications with a keen focus on security and reliability makes me an apt fit for your project. With me onboard, you can stay assured that your AWS deployment will be production-ready and secure while ensuring smooth running of the inference pipeline and report generation. Let's work together to turn your AWS infrastructure plans into reality!

@daxm0

Hi there, I’m excited about the opportunity to work on AWS Deployment of Dual-Model and believe my skills and experience make me a strong fit for this project. I clearly understand the core requirements of your project. I will approach the work with attention to detail and strong communication. The final delivery will reflect your vision and desired results. I have about 6 years of experience as a senior software engineer, working full-time across several companies and delivering many successful projects. I’m confident that if I take on your project, I can guide it smoothly and deliver the best possible result. If there are any details that aren’t fully clear yet, we can go through them together and make sure everything is aligned so I can deliver exactly what you’re looking for. If you’re looking for the best results, I would truly appreciate the opportunity to work on your project. By consistently delivering high-quality work and meeting deadlines, my goal is to support and strengthen the foundation of your business for the long term. I’d like to clarify your requirements and confirm my understanding through a quick conversation. Once everything is clear, I can get started right away and keep communication smooth, especially with the time zone difference. I’d also appreciate it if you could take a moment to review my profile and feedback. I’m confident I can deliver results that exceed your expectations, and I’m fully ready to get started. best regards, Dax M