Gen AI Engineer

Job Description

As a Generative AI Engineer, you will be responsible for designing, developing, and deploying generative AI models to solve complex business problems. You will work closely with data scientists, software engineers, and domain experts to build AI-driven applications that leverage LLMs, diffusion models, and other state-of-the-art generative AI techniques. Key Responsibilities Research, design, and develop generative AI models, including Large Language Models (LLMs), GANs, VAEs, and diffusion models. Fine-tune and optimize pre-trained models to meet business requirements. Collaborate with cross-functional teams to integrate AI models into production-ready applications. Develop scalable and efficient pipelines for data preprocessing, model training, and inference. Stay updated with the latest advancements in AI/ML and contribute to research initiatives. Ensure AI solutions are explainable, ethical, and comply with regulatory standards. Optimize model performance in terms of accuracy, latency, and cost-effectiveness. Implement and maintain MLOps best practices for continuous deployment and monitoring. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 3+ years of experience in AI/ML development, with at least 1+ year of hands-on experience in generative AI. Strong proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Exposure working with transformer-based architectures like GPT, BERT, and diffusion models. Solid understanding of deep learning, NLP, and computer vision techniques. Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with model deployment, APIs, and MLOps tools for CI/CD automation. Strong problem-solving skills and ability to work in an agile, collaborative environment. Preferred Qualifications Experience in fine-tuning and deploying LLMs such as GPT-4, LLaMA, or PaLM. Hands-on experience with reinforcement learning and prompt engineering. Understanding of Responsible AI principles and bias mitigation techniques.