Generative AI Developer

Role Overview: As a highly skilled Generative AI (GenAI) Developer, you will leverage your expertise in Google Cloud Platform (GCP), AI/ML frameworks, and modern development practices to design, develop, and deploy scalable AI/ML solutions. Your primary focus will be on Large Language Models (LLMs), NLP, and Generative AI applications. Collaborating with cross-functional teams, you will contribute to the creation of intelligent, data-driven systems that foster business innovation. Key Responsibilities: - Design, develop, and deploy GenAI-powered applications utilizing LLMs, NLP, and multimodal AI models. - Engage in the end-to-end AI/ML lifecycle, encompassing data preprocessing, model training, fine-tuning, evaluation, and deployment. - Utilize Google Cloud AI/ML services such as Vertex AI, AI Platform, BigQuery ML, and TensorFlow on GCP to build and optimize solutions. - Integrate GenAI models with APIs, microservices, and enterprise applications. - Create proof of concepts (POCs) and production-ready solutions for diverse AI/ML use cases. - Collaborate with data engineers, product managers, and business stakeholders to translate requirements into scalable AI solutions. - Ensure adherence to AI ethics, responsible AI practices, security protocols, and data governance standards. - Stay abreast of the latest advancements in AI, ML, and GenAI frameworks to drive continuous innovation. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. - Demonstrated experience (X+ years) in AI/ML development, emphasizing Generative AI and LLMs (e.g., GPT, PaLM, LLaMA, Claude, etc.). - Proficiency in GCP services such as Vertex AI, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, and AI/ML APIs. - Strong command of Python, SQL, and ML frameworks like TensorFlow, PyTorch, and Hugging Face Transformers. - Hands-on experience with fine-tuning, prompt engineering, embeddings, and model deployment. - Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps best practices. - Solid understanding of NLP, computer vision, or multimodal AI concepts. - Exceptional problem-solving skills, analytical thinking abilities, and effective communication capabilities. (Note: The job description does not contain any additional details about the company.),