Dimiour - Generative AI Engineer - Large Language Models

Responsibilities : - Design, develop, and implement Generative AI solutions, with a core focus on Large Language Models (LLMs). - Build and manage the infrastructure required for training, fine-tuning, and deploying LLMs in a scalable manner. - Utilize Python and relevant AI/GenAI frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers) for model development and experimentation. - Employ data manipulation libraries such as Pandas and NumPy for efficient data preprocessing and analysis crucial for GenAI models. - Develop robust and scalable APIs using FastAPI to expose GenAI models and functionalities to other applications and services. - Apply strong software engineering principles, including version control (Git), continuous integration and continuous deployment (CI/CD), and automated testing, throughout the GenAI solution development lifecycle. - Implement and manage MLOps workflows for the efficient deployment, monitoring, and maintenance of GenAI models in a production environment. - Utilize DevOps tools such as Docker, Kubernetes, Jenkins, and Terraform to automate infrastructure provisioning and application deployment for AI/GenAI solutions. - Implement and maintain advanced CI/CD pipelines to ensure the rapid and reliable delivery of GenAI applications. - Collaborate effectively with data scientists, researchers, and other engineers in a remote setting to translate business requirements into technical GenAI solutions. - Contribute to the design and architecture of our remote AI platform and infrastructure. - Stay up-to-date with the latest advancements in Generative AI, LLMs, MLOps, and related technologies. Skills Required : - 5 years of professional experience with a strong focus on Python development and AI/GenAI frameworks. - Proven expertise in implementing and managing Large Language Models (LLMs). - Strong proficiency in Python and experience with AI/GenAI frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers). - Extensive experience with data manipulation libraries such as Pandas and NumPy. - Solid experience in developing APIs using FastAPI. Comprehensive understanding of software engineering principles, including : - Version control using Git. - Continuous Integration and Continuous Deployment (CI/CD) practices. - Automated testing methodologies. - Essential experience in MLOps and ML Engineering, with a demonstrable track record of developing and maintaining AI solutions in production. - Proficiency in DevOps tools such as Docker, Kubernetes, Jenkins, and Terraform. - Experience implementing advanced CI/CD pipelines. - Excellent written and verbal communication skills for effective remote collaboration. - Ability to work independently and proactively in a remote environment. (ref:hirist.tech)

Location: in, IN

Posted Date: 5/7/2025