Job
Description
As a Gen AI Engineer , you will be responsible for developing, optimizing, and deploying AI models and solutions with a focus on Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG) models, and Large Language Models (LLMs). You will collaborate closely with cross-functional teams to design and implement scalable AI solutions on various cloud platforms. Key Responsibilities AI Model Development : Design, train, and fine-tune generative AI models, LLMs, and RAG models to address specific business use cases. Prompt Engineering : Develop, test, and optimize prompts to enhance the performance and accuracy of AI models in generating desired outputs. Cloud Expertise : Deploy and manage AI models on cloud platforms (e.g., AWS, Azure, GCP) ensuring scalability, security, and cost-efficiency. Data Management : Collaborate with data scientists and engineers to ensure high-quality data ingestion, preprocessing, and feature engineering. Model Evaluation & Tuning : Continuously monitor and evaluate model performance, making adjustments to improve accuracy and efficiency. Innovation : Stay up-to-date with the latest advancements in AI, LLMs, and cloud technologies, and incorporate new techniques and tools into the development process. Collaboration : Work closely with product managers, software engineers, and other stakeholders to integrate AI solutions into products and services. Documentation : Maintain comprehensive documentation of models, algorithms, and development processes to ensure transparency and : Education : Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or a related field. Experience : Proven experience in developing and deploying AI models, particularly in Generative AI, LLMs, and RAG models. Hands-on experience with cloud platforms like AWS, Azure, or GCP for AI/ML workloads. Strong background in Prompt Engineering and AI model optimization techniques. Technical Skills Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar frameworks. Experience with NLP, machine learning algorithms, and data preprocessing. Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus. Familiarity with MLOps practices and tools for continuous integration and deployment. Soft Skills Strong problem-solving skills and the ability to work in a fast-paced environment. Excellent communication and teamwork abilities. Eagerness to learn and adapt to new technologies and methodologies (ref:hirist.tech) Show more Show less
