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I will deploy, optimize and scale ai computer vision models on AWS sagemaker GPU
Patrick Mtrick
About this gig
Need to deploy AI or computer vision models on AWS SageMaker?
I help startups, enterprises, and AI teams deploy production-ready machine learning and computer vision solutions on AWS.
Whether you're experiencing high API latency, scalability issues, or need a dedicated GPU inference endpoint, I can design and deploy a secure, cost-effective, and scalable solution.
Services Include
AWS SageMaker Deployment
SAM2 & SAM3 Deployment
Computer Vision Solutions
GPU Endpoint Configuration
Docker Containerization
AWS Lambda Integration
API Gateway Setup
IAM & Security Configuration
CloudWatch Monitoring
Autoscaling Configuration
Cost Optimization
MLOps Best Practices
Supported Technologies
- AWS SageMaker
- AWS Lambda
- Amazon S3
- API Gateway
- IAM
- Docker
- PyTorch
- TensorFlow
- Hugging Face
- YOLO
- SAM2
- SAM3
- Computer Vision Models
Why Work With Me?
AWS Cloud Engineering Experience
Production-Focused Solutions
Scalable & Secure Architecture
Fast Communication
Clean Documentation
Business-Oriented Approach
Contact me before ordering
Get to know Patrick Mtrick
Patrick Mtrick
Solution Architect
- FromNetherlands
- Member sinceDec 2025
- Avg. response time1 hour
Languages
English, German, French, Spanish
Hello there! I’m an AWS and Web Solutions Expert with 5 years of experience helping clients build, manage, and optimize their cloud environments. I specialize in Amazon Web Services, PHP, and WordPress, offering complete infrastructure setup, troubleshooting, and performance optimization. Whether it’s deploying servers, configuring security, or fixing application errors, I ensure everything runs efficiently and securely. I enjoy working with clients, solving complex technical challenges, and staying up to date with the latest cloud technologies. Client satisfaction is always my top priority.
Other AI Development Services I Offer
FAQ
Q1: What models can you deploy?
I can deploy SAM2, SAM3, YOLO, Grounding DINO, Hugging Face models, PyTorch models, TensorFlow models, and custom computer vision or machine learning models on AWS SageMaker.
Q2: Do I need to have AWS infrastructure already set up?
No. I can help configure the required AWS resources including SageMaker, IAM roles, S3 buckets, networking, monitoring, and endpoint deployment.
Q3: Can you deploy models that are not running locally yet?
Yes. If you have the model repository or implementation details, I can assist with containerization, environment setup, deployment architecture, and inference endpoint configuration.
Q4: Can you help reduce inference latency from third-party APIs like Roboflow?
Yes. Many clients migrate from third-party inference APIs to dedicated SageMaker GPU endpoints to achieve lower latency, improved scalability, and greater control over their AI infrastructure.
Q5: What AWS services do you work with?
I work with AWS SageMaker, Lambda, API Gateway, S3, IAM, CloudWatch, ECS, EKS, VPC, Bedrock, DynamoDB, and other AWS services commonly used in AI and MLOps solutions.
