You will get Amazon SageMaker Deep Learning/Machine Learning Model Deployment (Training)
Project details
Deploying AWS SageMaker endpoints with precision, understanding your strategic vision, and consistently meeting industry benchmarks, my service elevates your machine-learning capabilities. For businesses seeking the fusion of technical excellence and strategic insight, this tailored SageMaker service offers a competitive edge. Partner with expertise that understands not just the how but also the why, ensuring your deployment functions seamlessly and resonates with your enterprise goals.
In the landscape of rapid technological evolution, it's not just about deploying machine learning solutions but about doing so with foresight and precision. My SageMaker deployment process is a reflection of that ethos. I don’t just provide technical solutions; I offer a partnership that understands the intricacies of your business objectives. This synergy of technological mastery and business acumen sets our service apart, ensuring your operations are efficient and strategically aligned with your vision. Experience the confluence of innovation and strategy, and elevate your business to the next level of excellence.
In the landscape of rapid technological evolution, it's not just about deploying machine learning solutions but about doing so with foresight and precision. My SageMaker deployment process is a reflection of that ethos. I don’t just provide technical solutions; I offer a partnership that understands the intricacies of your business objectives. This synergy of technological mastery and business acumen sets our service apart, ensuring your operations are efficient and strategically aligned with your vision. Experience the confluence of innovation and strategy, and elevate your business to the next level of excellence.
Machine Learning Tools
Amazon SageMaker, BERT, Keras, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$400
|
Standard
$800
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 20 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Scenarios | 1 | 2 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Performance Optimization
(+ 5 Days)
+$450
Integration with Other AWS Services
(+ 5 Days)
+$400
Amazon Sagemaker Training
(+ 10 Days)
+$1,000Frequently asked questions
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SA
Steve A.
Oct 8, 2025
Sagemaker Consulting - One Hour To Start
Excellent work
SM
Seth M.
Jan 26, 2025
Sagemaker Deploy and Setup
I will say finding real talent on Upwork is challenging who are genuinely senior, gifted and capable. Rafal is that resource. Extremely experienced, the real deal and he shows up like an owner not a contractor. He calls out things that don’t make sense and pushes for the right solution especially in teams. Strongly recommend
AH
Adam H.
Jan 24, 2025
30 minute consultation
Rafal has an incredibly strong command of his area of expertise. He was extremely helpful in not only fulfilling the goal but in bringing me along on the learning journey. I would highly recommend him.
RM
Ricards M.
Sep 11, 2024
Code review and development
True professional. Fast, clever and always goes for the solution, helped us to solve big challenge that no one else could.. Higly recommend.
BO
Bert O.
Mar 24, 2024
Sagemaker ML pipeline creation consultation
Rafal was very helpful! I appreciated how everything was broken down and explained. I had a goal in mind and Rafal was able to help me visualize the architecture needed and pull to make it happen.
About Rafal
AI/ML Engineer | Computer Vision & AWS SageMaker Specialist
100%
Job Success
Rzeszow, Poland - 2:37 am local time
Business-Centric Development: I deeply understand your business to craft solutions that align perfectly with your challenges and opportunities, ensuring innovation is impactful and economical.
Complimentary Consultation: Begin our collaboration with clarity. Schedule a one-hour consultation to discuss your needs and how I can contribute.
Resourceful Execution: Equipped with a high-performance server optimized for training deep learning models, including medium-scale object detection and transfer learning for LLM models.
Measurable Results: My projects consistently yield tangible outcomes, from optimized inference times to high-throughput video analysis.
📈 Achievements By The Numbers
🚦 Object Detection & Cloud:
Traffic Analytics Development: Led software development using NVIDIA DeepStream with multi-stage models on 100+ sites featuring several cameras each, leveraging NVIDIA Jetson devices and TensorRT for optimized performance.
Advanced MLOps Pipelines: Managed MLOps pipelines, achieving 98% average accuracy in object detection models both on-premises and with AWS SageMaker.
Auto-Labeling Pipelines: Engineered rapid auto-labeling pipelines with Label Studio, curating a diverse dataset of 500K images in under six months.
Blurring Object Detection Models: Streamlined models via SageMaker and DeepStream, reducing response time by fivefold.
Semantic Segmentation: Executed on 5+ dashcam views with DeepStream, ensuring 25 fps per camera on Jetson devices.
High-Capacity Video Analysis: Deployed endpoints on SageMaker, processing over 1,000 videos weekly with 90% accuracy while cutting costs by 90%.
Sports Tennis Tracking Project: Developed a real-time tennis tracking system using advanced object detection algorithms and OpenCV, enhancing player performance analysis.
🔍 Anomaly Detection:
Production Deployment: Spearheaded the deployment of anomaly detection algorithms on 10+ production sites using Raspberry Pi, analyzing over 30,000 signals daily.
AWS SageMaker Canvas Integration: Leveraged SageMaker Canvas for rapid Development and deployment of anomaly detection models.
Price Trading Anomaly Detection: Implemented anomaly detection for price trading on AWS, utilizing SageMaker and PyOD to identify irregularities in financial data.
☁ AWS Mastery:
Serverless Systems Development: Built scalable, serverless systems using AWS ECS, S3, Lambda, DynamoDB, and RDS, enabling efficient data processing solutions.
Data Pipelines: Orchestrated serverless pipelines processing over 500K data records daily.
Efficient SageMaker Endpoints: Crafted data pipelines for 10+ SageMaker endpoints, achieving near-instant processing with S3 triggers.
Video Analysis Optimization: Optimized video analysis via SageMaker's autoscaling endpoint, reducing processing times by 80% and costs by 90% through effective scaling.
Real-Time Data Processing: Innovated a robust system based on DynamoDB, AppSync, S3, and RDS, overseeing over 1M+ data transactions daily.
🎨 Generative AI Enthusiast
My passion drives my expertise. I have hands-on experience using the OpenAI API, Hugging Face, and LangChain, constantly pushing the boundaries of AI.
🔄 Versatile Approach
Whether embracing a startup's agility or an enterprise's consistency, I adapt to deliver the best of both worlds.
🛠️ Toolbox
🔑 Languages: Python
🌩️ Cloud: AWS SageMaker, AWS SageMaker Canvas, AWS ECS, AWS Lambda, AWS DynamoDB, AWS RDS, AWS S3, AWS Athena, Serverless Framework, AWS Glue, Amazon Redshift
🤖 Machine Learning: scikit-learn, pandas, numpy, PyCaret, PyOD, Plotly
🧠 Deep Learning: TensorFlow, PyTorch, NVIDIA TensorRT, DeepStream, OpenCV
📊 Data Science Specialties: Object Detection, Anomaly Detection, Semantic Segmentation, Generative AI
🚀 Misc. Tools: Ubuntu, Docker, SQL, CI/CD, Git, AWS CloudFormation
Certifications
AWS Certified Machine Learning – Specialty
Academy Accreditation - Databricks Lakehouse
AWS Certified Developer – Associate
Eager to bring unparalleled data-driven innovation to your challenges? Let's create the next success story together!
Steps for completing your project
After purchasing the project, send requirements so Rafal can start the project.
Delivery time starts when Rafal receives requirements from you.
Rafal works on your project following the steps below.
Revisions may occur after the delivery date.
Understanding Business Requirements
I'll discuss with you or designated stakeholders to understand the specific business objectives you aim to achieve with the SageMaker endpoint deployment. This ensures that the technical deployment perfectly aligns with your goals.
Environment Setup & Configuration
Initialize the AWS SageMaker environment. This involves setting up the necessary libraries, frameworks, dependencies, and IAM roles and permissions for secure and streamlined access.