Key skills
AWSCloudEC2PythonPyTorchAIMachine LearningMLDeep LearningComputer VisionMLOpsDatabricksS3SageMakerCI/CD
About this role
Role Overview
- Design, develop, and optimize machine learning and deep learning models using PyTorch
- Build and deploy computer vision solutions for real-world use cases
- Develop end-to-end ML pipelines, including data ingestion, preprocessing, training, validation, and deployment
- Implement and maintain MLOps workflows for model versioning, monitoring, CI/CD, and retraining
- Deploy and scale ML models on AWS cloud infrastructure
- Work with large-scale datasets using Databricks and distributed computing frameworks
- Collaborate with data scientists, product managers, and software engineers to translate business requirements into AI solutions
- Ensure high code quality by following software engineering best practices
- Monitor model performance in production and continuously improve accuracy, efficiency, and reliability
Requirements
- 5+ years of experience in AI/ML engineering
- Strong proficiency in Python
- Hands-on experience with PyTorch
- Solid understanding of deep learning architectures (CNNs, transfer learning, etc.)
- Practical experience in computer vision applications
- Experience working with Databricks and large-scale data processing
- Strong knowledge of AWS services for ML deployment (EC2, S3, SageMaker, etc.)
- Experience with MLOps tools and practices
- Good understanding of software engineering principles
Tech Stack
- AWS
- Cloud
- EC2
- Python
- PyTorch