Machine Learning Engineer
2 weeks ago
Description : We are seeking an experienced Machine Learning Engineer with strong expertise in Generative AI (GenAI) and payment data analytics to join our team. In this role, you'll work on large-scale credit card and UPI transaction data to identify use cases, develop PoCs, and build production-ready ML and GenAI solutions that unlock insights and drive innovation in payments. Key Responsibilities : Data Handling & Feature Engineering : - Collect, preprocess, and analyze payment datasets (credit card, UPI) to extract meaningful features, including embeddings, time-series signals, and customer behavior patterns. ML Model Development : - Design and implement models for fraud detection, customer segmentation, and demand forecasting using tools like TensorFlow, PyTorch, and Scikit-learn. - Generative AI & Foundation Models : Apply and fine-tune OSS LLMs (e.g., Hugging Face Transformers, Llama, GPT-J, Falcon) for use cases such as : - Synthetic data generation - Transaction summarization - Conversational AI for payment-related queries - Model Evaluation & Optimization : Use metrics like AUC-ROC, precision, recall, and F1-score to evaluate models. Apply hyperparameter tuning and distributed training for performance improvement.- Deployment & MLOps : Deploy ML/GenAI models using tools like MLflow, Kubeflow, SageMaker, and Docker/Kubernetes. Set up real-time inference pipelines and monitor model drift and reliability in production. - Collaboration & Communication : Work with cross-functional teams (data scientists, engineers, product) to define requirements and deliver business-impacting solutions. Present findings to both technical and non-technical stakeholders. Requirements : - Bachelors or masters degree in computer science, engineering, mathematics, statistics, or a related field. - 8 - 10 years of proven experience as a Machine Learning Engineer, Data Scientist, or similar role. - Strong knowledge of machine learning, statistics, and data science concepts and techniques. - Proficient in programming languages such as Python, R, and Java. - Experience with data processing tools like SQL, Spark, and Hadoop. - Proficient in using frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and other OSS LLMs. - Hands-on experience with foundational models, such as BERT, GPT, T5, and Vision Transformers (ViT). - Experience with credit card and UPI payment data use cases (e.g., fraud detection, transaction risk assessment, customer analytics) is a plus. - Experience fine-tuning and deploying OSS LLMs for specific tasks such as text summarization, synthetic data generation, and NLP applications in payments. - Familiarity with frameworks/tools like Hugging Face, LangChain, and LlamaIndex. - Hands-on experience deploying ML and GenAI models in production environments with tools like MLflow, Kubeflow, Docker, and Kubernetes. - Excellent communication and presentation skills, with the ability to explain complex concepts (ref:hirist.tech)
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