Senior Machine Learning Engineer

At CredArtha, we are revolutionizing financial intelligence with FINA (Financial Intelligence & Neural Analyst), our proprietary vertical LLM designed to process, analyze, and generate financial insights. Our mission is to empower financial institutions, businesses, and individuals with AI-driven precision, efficiency, and automation in financial decision-making. We are looking for a Senior Machine Learning Engineer who is passionate about LLMs, deep learning, and NLP and is eager to build cutting-edge AI models tailored for financial data processing, document understanding, and predictive analytics. If you have expertise in training and fine-tuning open-source LLMs, developing retrieval-augmented generation (RAG) systems, and optimizing NLP models for real-world applications, we want you on our team. As a Senior Machine Learning Engineer, you will: LLM Development & Optimization - Design, train, and fine-tune FINA, leveraging open-source LLMs such as LLaMA, Falcon, Mistral, and GPT-J for financial applications. - Implement parameter-efficient fine-tuning (PEFT) techniques to optimize model efficiency while maintaining accuracy. - Work on self-learning mechanisms to ensure FINA continuously evolves through user interactions and real-time financial data ingestion. NLP & Financial Data Processing - Develop and enhance NLP models for document understanding, financial risk analysis, and transaction categorization. - Work on named entity recognition (NER), sentiment analysis, topic modeling, and automated financial report generation. - Design embedding models and vector search architectures to create a robust financial knowledge base. RAG & AI-Powered Financial Insights - Implement retrieval-augmented generation (RAG) pipelines to enhance LLM response accuracy and domain knowledge. - Build custom search and retrieval mechanisms using vector databases like FAISS, Weaviate, or ChromaDB. - Develop multi-modal AI models that combine structured and unstructured financial data to provide deep insights and analytics. Deployment, MLOps & Scalability - Deploy and manage FINA using cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and MLOps best practices. - Optimize models for low-latency inference and scalability using quantization, distillation, and model pruning techniques. - Implement real-time monitoring and feedback loops to improve model performance and user experience. Ideal Candidate Profile We are looking for someone who has: - Hands-on experience in Machine Learning, Deep Learning, and NLP (LLMs, Transformers, RNNs, etc.). - Strong proficiency in Python, with experience in TensorFlow, PyTorch, Hugging Face Transformers, and LangChain. - Expertise in fine-tuning LLMs, self-supervised learning, and AI explainability. - Experience working with financial data (bank statements, credit reports, transactional data, risk models, etc.). - Strong knowledge of vector embeddings, search algorithms, and RAG implementations. - Familiarity with database technologies (SQL, MongoDB, NoSQL) and cloud platforms (AWS, GCP, Azure). Bonus: Experience in financial risk modeling, fraud detection, or credit scoring models. Why Join CredArtha - Innovate at the intersection of AI & Finance. Work on groundbreaking AI-driven financial solutions. - Build FINA from the ground up. Develop a vertical LLM that will be at the core of CredArtha's technology stack. - Impact millions. Help businesses and financial institutions automate, analyze, and optimize decision-making with AI. - Freedom to experiment. Push the boundaries of deep learning and NLP in a fast-paced, innovation-driven environment.,