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About the role
You are someone with a good understanding of the architecture underlying large language models, such as Transformer-based models, including GPT and their variants. You have experience in training large-scale language models from scratch, as well as fine-tuning pre-trained models on domain data. Your skills include preprocessing textual data, such as tokenization, stemming, lemmatization, and handling different text encoding. You are proficient in applying transfer learning techniques to adapt existing LLMs to new languages, domains, or specific business needs. You have the ability to design models that effectively handle ambiguities, nuances, and context in NLP. Additionally, you possess skills in designing and implementing data annotation strategies for training LLMs and evaluating their performance using appropriate metrics. You also have experience in scaling LLMs for production environments, ensuring efficiency and robustness in deployment. What You Will Do: - Model Training, Optimization, and Evaluation: This encompasses the complete cycle of training, fine-tuning, and validating language models. You will be designing and adapting LLMs for use in virtual assistants, Information retrieval, and extraction, etc. - Experimentation with Emerging Technologies and Methods: Actively exploring new technologies and methodologies in language model development, including experimental frameworks and software tools. Basic Qualifications: - 5 years of experience writing code using Python - 5 years of experience in natural language processing tools, including working with large language models, text classification, natural language generation - MS degree with 3 years of experience as a machine learning engineer or researcher Preferred Qualifications: - A thorough understanding of machine learning, particularly deep learning techniques, including knowledge of neural network architectures, training methods, and optimization algorithms - Knowledge and practical experience in NLP techniques and tools, including working with language models, text classification, and natural language generation - Experience with frameworks: PyTorch, or Keras - Skills in data preprocessing, cleaning, and analysis, with the ability to work with large datasets and extract meaningful insights - The capacity to think critically and tackle complex, innovative problems in the field - Willingness to continuously learn and adapt, crucial in the ever-evolving field of AI At Alphastream.ai, we offer a dynamic and inclusive workplace where your skills are valued, and your career can flourish. Enjoy competitive compensation, a comprehensive benefits package, and opportunities for professional growth. Immerse yourself in an innovative work environment, maintain a healthy work-life balance, and contribute to a diverse and inclusive culture. Join us to work with cutting-edge technology and be part of a team that recognizes and rewards your achievements, all while fostering a fun and engaging workplace culture. Alphastream.ai envisions a dynamic future for the financial world, where innovation is propelled by state-of-the-art AI technology and enriched by a profound understanding of credit and fixed-income research. Our mission is to empower asset managers, research firms, hedge funds, banks, and investors with smarter, faster, and curated data. We provide accurate, timely information, analytics, and tools across simple to complex financial and non-financial data, enhancing decision-making. With a focus on bonds, loans, financials, and sustainability, we offer near real-time data via APIs and PaaS (Platform as a Service) solutions that act as the bridge between our offerings and seamless workflow integration. To learn more about us, visit Alphastream.ai. You are someone with a good understanding of the architecture underlying large language models, such as Transformer-based models, including GPT and their variants. You have experience in training large-scale language models from scratch, as well as fine-tuning pre-trained models on domain data. Your skills include preprocessing textual data, such as tokenization, stemming, lemmatization, and handling different text encoding. You are proficient in applying transfer learning techniques to adapt existing LLMs to new languages, domains, or specific business needs. You have the ability to design models that effectively handle ambiguities, nuances, and context in NLP. Additionally, you possess skills in designing and implementing data annotation strategies for training LLMs and evaluating their performance using appropriate metrics. You also have experience in scaling LLMs for production environments, ensuring efficiency and robustness in deployment. What You Will Do: - Model Training, Optimization, and Evaluation: This encompasses the complete cycle of training, fine-tuning, and validating language models. You will be designing and adapting LLMs for use in virtu