• Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency.
• Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems.
• 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.
• Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment.
• Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries.
• Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills.
• Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security.
• Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments.

Required Technical and Professional Expertise
1.Programming Proficiency:

• Proficiency in Python, C++.
• Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products.

2.Data Handling Skills:

• Skilled in integrating, cleansing, and shaping data.
• Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.

3.DevOps Experience:

• Experienced in DevOps practices.

• Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes).

4.Open-Source Contribution:

• Open-source Contribution is a plus.
• Experience in contributing to open-source AI projects or utilizing open-source AI frameworks.

5.Problem-Solving Skills:

• Strong problem-solving and analytical skills.
• Experience in optimizing AI algorithms for performance and scalability.

6.AI Compiler/Runtime Skills:

• AI compiler/runtime skills would be a plus.

7.Agile Methodologies:

• Familiarity with Agile methodologies.
• Experience in Agile development of AI-based solutions.
• Ensuring efficient project delivery through iterative development processes

Preferred Technical and Professional Expertise

• Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively.
• Proficiency in distributed systems, microservice architecture, and REST APIs.
• Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows.
• Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies.
• Proven ability to contribute to the development and improvement of AI frameworks and libraries.
• Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders.
• Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams.
• Proven track record of ensuring compliance with industry best practices and standards in AI engineering.
• Maintained high standards of code quality, performance, and security in AI projects.
• Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.