Job title: Gen AI/ML Python Engineer Location: New York, NY (Onsite) 12 Months Contract Banking Experience is Must We are seeking a Machine Learning / Generative AI Engineer with expertise in Python to join our innovative team. The ideal candidate will have a deep understanding of modern machine learning methods, especially in generative AI (such as LLMs, diffusion models, etc.), and demonstrate strong proficiency in Python-based development for scalable ML workflows. Responsibilities Design, build, and deploy machine learning and generative AI models using state-of-the-art architectures. Collaborate with data scientists, researchers, and product teams to conceptualize and implement AI-driven features and solutions. Develop robust and maintainable Python code for data preprocessing, model training, evaluation, deployment, and monitoring. Stay current with advancements in ML and Gen AI communities and evaluate emerging techniques for applicability. Optimize models for performance, scalability, and efficiency in production environments. Document processes, model architectures, and share knowledge with team members. Requirements Bachelor's or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field. Demonstrable experience with modern machine learning frameworks (e.g., TensorFlow, PyTorch, JAX) and tools for generative AI. Proficient in Python for data engineering, ML pipelines, and software engineering best practices. Solid understanding of deep learning, neural networks, and generative model concepts (GANs, VAEs, LLMs, diffusion models). Experience working with large datasets, feature engineering, and data labeling. Familiarity with MLOps concepts, versioning, and collaborative workflows (Docker, Git, CI/CD pipelines). Strong problem-solving skills and the ability to communicate complex technical topics clearly. Preferred Qualifications Published work or contributions to open-source ML/AI projects. Experience deploying large models in cloud or distributed environments (AWS, GCP, Azure, etc.). Experience with model compression, distillation, or optimization techniques.