Artificial Intelligence / Machine Learning Engineer

Role Description:

The AI Engineer is responsible for the deployment, integration, and enhancement of the organization’s artificial intelligence, machine learning models and advanced analytics artifacts. The candidate works with the business analysts, applications consultants, data scientists, data engineers, and DevOps engineers in order to understand and lead the introduction and integration of artificial intelligence / machine learning (AI/ML) models to support business requirements and enhancements in multiple industries and scenarios.

Responsibilities:

• Understand business problems and select the best AI approach and models to solve them through experimentation and evaluation metrics.
• Use machine learning techniques like transfer learning, fine-tuning, prompt engineering to tweak pre-trained AI models to specific use case or task.
• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries .
• Recommend and provision the technology infrastructure required for AI models training, fine-tuning, and serving.
• Operationalize AI/ML models for both online scoring and batch scoring using containerization, APIs development, and scheduled jobs.
• Automate the deployment of AI/ML models using techniques like MLOps, AIOps, and ModelOps
• Lead and train junior team members
• Develop and maintain technical documentation and operation manuals.

Qualifications:

• Bachelor's degree in fields like Computer Science, Computer Engineering, Business Analytics, or a related field.
• Master’s degree in Artificial Intelligence or Software Engineering is preferred
• Advanced working knowledge and experience in APIs integration and software development
• Advanced working knowledge and experience using Python and C#
• Experience in AI/ML development using libraries like scikit-learn, TensorFlow, and PyTorch
• Experience in working with structured, semi-structured, and unstructured data
• Experience in using Agile and DevOps practices for software applications delivery.
• Must have a strong understanding of CI/CD practices and technologies specifically Azure DevOps
• Coding knowledge and experience with several languages and IDEs like Node, JavaScript, VS Code
• Experience using Microsoft Azure storage and services is a plus.

Required Experience:

• 5+ years hands-on data science / AI /ML experience
• Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
• Test-driven development (prefer py. test/nose), experience with Cloud environments
• Open-source GenAI production deployment and monitoring (both on-prem and cloud)
• RAG applications development, evaluation, and production deployment
• Vector Databases
• GenAI frameworks and toolset: Langchain, LlamaIndex, etc.
• AI Agentic workflows