What are the responsibilities and job description for the AI Engineering Lead position at INUIX Consulting?
Job Details
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.