Machine Learning Engineer - Generative AI

<p><p><b>Role Overview :</b><br/><br/>We are seeking a versatile ML Engineer with strong expertise in deploying ML, AI, and GenAI models on the Snowflake platform.<br/><br/> The ideal candidate will have hands-on experience with Snowflake Cortex, building and managing ML pipelines, and utilizing tools like MLflow within DevOps and CI/CD environments.<br/><br/> Mastery of Python, SQL, Docker, and Snowpark development is essential to engineer scalable, performant AI/ML workflows.<br/><br/> Exposure to automated code review tools like Linting and Black will further enhance code quality and maintainability.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Architect, develop, and deploy machine learning and Generative AI models leveraging Snowflake and its Cortex capabilities.<br/><br/>- Build, automate, and manage robust ML pipelines incorporating tracking, versioning, and model lifecycle management using tools like MLflow.<br/><br/>- Implement DevOps best practices and enable CI/CD pipelines for smooth, automated model deployment and updates.<br/><br/>- Develop reusable components and business logic using Python, SQL, and Snowpark for efficient model training and inference.<br/><br/>- Containerize ML projects with Docker to ensure reproducibility, portability, and scalable production deployments.<br/><br/>- Integrate and enforce automated code review processes using tools such as Linting and Black to maintain high code standards.<br/><br/>- Collaborate with data scientists, engineers, and infrastructure teams to optimize resource usage, model performance, and operational reliability.<br/><br/>- Monitor model health, schedule retraining, and troubleshoot production issues to ensure continuous AI service quality.<br/><br/><b>Required Skills and Qualifications :</b><br/><br/>- Strong proficiency in Python, SQL, Docker, and hands-on experience with Snowpark for building data and ML components.<br/><br/>- Experience deploying and managing ML/AI/GenAI models on the Snowflake platform, with knowledge of Snowflake Cortex.<br/><br/>- Familiarity with MLflow or similar model management tools and ability to drive end-to-end ML pipelines.<br/><br/>- Understanding of DevOps practices and CI/CD pipelines tailored to AI/ML workflows.<br/><br/>- Exposure to automated code quality tools such as Linting and Black is highly desirable.<br/><br/>- Strong collaboration, problem-solving skills, and ability to work in complex, fast-paced environments.<br/><br/><b>Recommended Experience :</b><br/><br/>- 4 to 8 years of relevant experience in ML engineering, data engineering, or AI product development roles with a focus on cloud-native data platforms</p><br/></p> (ref:hirist.tech)