Associate Architect - AI/ML

As a Senior AI/ML Engineer, you will be responsible for designing, developing, and deploying advanced AI models with a focus on generative AI, including transformer architectures such as GPT, BERT, T5, and other deep learning models utilized for text, image, or multimodal generation. You will work with extensive and complex datasets by cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Additionally, you will collaborate with cross-functional teams to identify project objectives and create solutions using generative AI tailored to business needs. Your role will involve implementing, fine-tuning, and scaling generative AI models in production environments to ensure robust model performance and efficient resource utilization. You will also be responsible for developing pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. It is essential to stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Furthermore, documenting and communicating technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders with an emphasis on explainability and responsible AI practices. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. A relevant Ph.D. or research experience in generative AI would be advantageous. You should have 12-16 years of experience in machine learning, with at least 8 years in designing and implementing generative AI models or working specifically with transformer-based models. The ideal candidate will possess expertise in generative AI, transformer models, GANs, VAEs, text generation, and image generation. Strong knowledge of machine learning algorithms, deep learning, neural networks, and programming skills in Python and SQL are required. Familiarity with libraries such as Hugging Face Transformers, PyTorch, TensorFlow, and experience with MLOps tools like Docker, Kubernetes, MLflow, and Cloud Platforms (AWS, GCP, Azure) is essential. Additionally, proficiency in data engineering concepts such as data preprocessing, feature engineering, and data cleaning is preferred. Joining our team will provide you with an opportunity to work on technical challenges with global impact, vast opportunities for self-development through online university access and sponsored certifications, sponsored Tech Talks & Hackathons, and a generous benefits package including health insurance, retirement benefits, flexible work hours, and more. You will work in a supportive environment with forums to explore passions beyond work, offering an exciting opportunity to contribute to cutting-edge solutions while advancing your career in a dynamic and collaborative setting.,