Overview
Skills
Job Details
****Client is not sponsoring any visa****
AI Engineering Lead
Must Have Technical/Functional Skills
- Strong proficiency in Python for AI/ML development.
- Hands-on experience with OpenAI and modern AI frameworks.
- Experience with AWS services for AI deployment.
- Proven leadership and ability to guide engineering teams
Good to have
- Solid understanding of ETL processes and data integration.
- Airflow and Harness for managing AI pipelines.
- Familiarity with platforms for data management.
- Familiarity with automated testing and deployment pipelines.
Roles & Responsibilities
Build and maintain AI/ML pipelines on AWS, leveraging services such as Amazon S3 for data storage, AWS Lambda for
serverless functions, and Amazon EC2 for compute resources.
Deploy trained models into production environments using AWS SageMaker Endpoints, AWS Lambda, or containerization technologies like Docker and Kubernetes on AWS EKS.
Implement MLOps practices for continuous integration, continuous delivery (CI/CD), and monitoring of ML models.
Preprocess and analyze data, engineer features, and select appropriate algorithms for specific problems.
Utilize AWS services like Amazon SageMaker for efficient model training, hyperparameter tuning, and experiment
tracking.
Analyzes data, builds models, and uncovers insights, often using Python for exploration and prototyping.