Principal machine learning engineer

Principal Machine Learning Engineer

Informatica is on a journey to leverage generative AI to simplify cloud data management. Principal Machine Learning Engineer will be responsible for driving the overall architecture and pipelines to enable Machine Learning engineers to build, train and deploy Models at scale across multiple cloud services providers in a cloud agnostic manner. This role is highly visible and critical to leapfrog Informatica's AI journey.

Responsibilities :

Design and Implement end to end AI based Saa S for enterprises

Drive architecture and design for AI and ML related model pipelines, and services

Collaborate closely with cross-functional internal teams, including stakeholders, to identify opportunities for developing end-to-end AI architectures for diverse industry scenarios.

Passion for applying state-of-the art AI algorithms to real-world problems.

Stay up-to-date with the latest developments in AI and related fields, evaluate new developments and technologies for potential integration into existing and future architecture

Responsible for providing solutions that foster ML Engineer developer productivity.

Lead the development and deployment of machine learning models, deep learning algorithms, and other AI / ML techniques. Ensure best practices for model training, testing, and validation are followed.

Requirements :

Solid First Principles thinking for Data and AI

Solid understanding and hands-on experience developing ML models ranging from regression to deep neural networks including LLMs

Solid understanding of data engineering principles, adapting data for AI

Solid understanding of AI / ML frameworks and skills to do rapid prototypes

Familiarity with modern techniques for Language Understanding, and other Machine Learning and AI technologies

Collaborate with local and global team of engineers, researchers, and product managers.

Masters degree in Computer Science, Electrical Engineering or related fields with focus on AI and machine learning.

10+ years of industry and research experience in Artificial Intelligence and Machine Learning

Experience with AWS, Google or Azure is Required

Experience and understanding of modern ML pipelines using Kubeflow, KServe, Hugging Face, and similar toolkits is preferred.