Applied AI Engineer II

This is a fully remote position, open to applicants in India.

📋 Description

• Work alongside seasoned data scientists and software engineers to gather insights for creating scalable and efficient data pipelines, as well as model training and deployment systems.

• Diagnose issues throughout the entire machine learning infrastructure, from Linux and Docker to Kubernetes, and at the top levels of our ML stack. Resolve challenges, enhance system performance, and strive to make our stack the industry leader.

• Support the design and development of on-premises MLOps solutions that facilitate the delivery of machine learning models, ensuring a smooth transition between research and the productionization of ML artifacts.

• Promote and maintain high engineering standards, ensuring consistency across codebases and confirming that software undergoes thorough review, testing, and integration.

• Enhance existing models to improve performance and throughput.

• Implement ML model training, validation, and evaluation configurations alongside traditional coding assessments such as unit and integration testing.

• Develop and sustain tools for deployment, monitoring, and operational tasks.

• Continuously improve and upgrade CI/CD workflows to meet the changing demands of the machine learning infrastructure.

⛳️ Requirements

• Minimum of 3 years of experience in MLOps or full-stack Machine Learning.

• Proficient programming abilities in a contemporary programming language (Python, Scientific Python Stack, Cuda).

• Familiarity with the MLOps life cycle and practical experience with MLOps workflows.

• Knowledge of industry-standard tools and practices, including Kubernetes, GCP/AWS/Azure, CI/CD, popular ML frameworks, and data management.

• A strong interest in machine learning engineering with a proactive approach to exploring effective scaling methods.

• A genuine desire to learn, coupled with excellent communication skills and enthusiasm for collaborative problem-solving.

🏝️ Benefits

• Competitive salary and comprehensive benefits package.

• Opportunities for professional development and career advancement.

• Access to cutting-edge technology and tools in the field of machine learning.

• Supportive and innovative work environment that values teamwork and creativity.