AI Engineer

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency.

2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems.

3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs.

4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment.

5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries.

6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills.

7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security.

8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments.