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. Your Role & Responsibilities 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.,

About Calaxis by Credartha Calaxis by Credartha is on a mission to unchain AI development. We believe the $15 trillion promise of AI is being held hostage by a broken, fragmented, and prohibitively expensive development process. Our integrated pipeline is engineered to master data and empower organizations to own their future by building trustworthy, domain-specific AI. We are eliminating the bottlenecks of slow, biased, and unscalable manual annotation by pioneering a new method. Our core innovation, the "Council of Judges," automates expert data validation, replacing human armies with a cascade of specialized AI models to deliver systematic, scalable quality assurance. The Role We are looking for a pioneering Data Science Researcher to be the engine of our innovation and the architect of our technological advantage. You will be responsible for advancing the core intellectual property that underpins our entire platform. This role goes beyond applying existing models; you will be conducting foundational research to build, refine, and scale our proprietary methodologies, including our "Council of Judges" and our "Deeptech Self-Improving Flywheel". Your work will directly contribute to keeping Calaxis at the forefront of the AI evolution, ensuring our methods remain more efficient and powerful than the capital-intensive approaches that dominate the market. If you are driven to solve the most challenging problems in AI data generation, validation, and model improvement, and want to see your research have a direct commercial impact, this role is for you. What You'll Do: Lead foundational research and development of our "Council of Judges" AI, including advancing our proprietary "Two-Tiered" training paradigm. Design and implement novel algorithms and experiments to enhance the "Deeptech Self-Improving Flywheel," ensuring our entire system becomes more intelligent and efficient over time. Spearhead the research, testing, and integration of advanced Reinforcement Learning (RL) techniques to enhance our data generation and validation capabilities. Drive the continued development of our custom architectures, including our Multimodal LLM (VLM) for interpreting visual data and our Retrieval-Augmented Generation (RAG) pipeline. Innovate on our Central Dataset Generator to improve the quality and complexity of our automatically generated instruction-following datasets. Develop new methods for automated data validation and quality assurance, pushing the boundaries of what is possible in building trustworthy AI. Publish your findings in top-tier AI conferences and journals, establishing Calaxis as a thought leader in the industry. Collaborate closely with the engineering team to translate cutting-edge research into robust, scalable components of our production platform. Who You Are: You possess a Ph.D. , Master's or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, with a strong publication record. You have proven experience in conducting original research in Natural Language Processing (NLP), and Machine Learning, particularly with Large Language Models (LLMs). You have deep expertise in areas such as Reinforcement Learning (especially RLHF), model fine-tuning, retrieval-augmented generation (RAG), and data generation techniques. Experience with multimodal models (V)LM is a significant advantage. You are a master of scientific programming with expert-level skills in Python and deep learning frameworks like PyTorch or TensorFlow. You have a pioneering mindset and are driven by the challenge of creating new methods, not just applying existing ones. You are capable of working independently to define research problems and see them through to production-ready solutions. Why Join Calaxis? This is a rare opportunity to shape the core technology of a company set to redefine the AI development lifecycle. At Calaxis, your research will not be a theoretical exercise; it will be the "core IP" that drives our business. You will have the resources and autonomy to pursue breakthrough ideas and see them deployed on a platform designed to impact every major industry vertical. Join us and build the future of AI.