AI/ML Generative Model Developer

As a Machine Learning Engineer with a focus on generative models, your role will involve the following responsibilities: - Utilizing your 4+ years of experience in machine learning, deep learning, or AI research, particularly focusing on generative models. - Applying your expertise with generative models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models such as GPT-3/4, BERT, DALL.E. - Demonstrating an understanding of model fine-tuning, transfer learning, and prompt engineering within the context of large language models (LLMs). - Applying your knowledge of reinforcement learning (RL) and other advanced machine learning techniques for generative tasks. - Showcasing your strong programming skills in Python and familiarity with relevant libraries and frameworks. - Demonstrating proven experience in document detail extraction and feature engineering. - Proficiently utilizing data processing and manipulation techniques. - Building data applications using Streamlit or similar tools. - Demonstrating advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Using your problem-solving skills to work effectively in a collaborative environment. - Communicating complex technical concepts to non-technical stakeholders effectively. Qualifications required for this role include: - 4+ years of experience in machine learning, deep learning, or AI research. - Strong programming skills in Python and familiarity with relevant libraries and frameworks. - Proven experience in document detail extraction and feature engineering. - Proficiency in data processing and manipulation techniques. - Hands-on experience in building data applications using Streamlit or similar tools. - Advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Excellent problem-solving skills and the ability to work effectively in a collaborative environment. - Robust communication skills to convey complex technical concepts to non-technical stakeholders. It would be good to have the following additional skills and experiences: - Experience in the banking/financial services/industry-specific sector. - Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP. - Proven experience working with OpenAI or similar large language models (LLMs). - Certifications in Data Science, Machine Learning, or AI. As a Machine Learning Engineer with a focus on generative models, your role will involve the following responsibilities: - Utilizing your 4+ years of experience in machine learning, deep learning, or AI research, particularly focusing on generative models. - Applying your expertise with generative models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models such as GPT-3/4, BERT, DALL.E. - Demonstrating an understanding of model fine-tuning, transfer learning, and prompt engineering within the context of large language models (LLMs). - Applying your knowledge of reinforcement learning (RL) and other advanced machine learning techniques for generative tasks. - Showcasing your strong programming skills in Python and familiarity with relevant libraries and frameworks. - Demonstrating proven experience in document detail extraction and feature engineering. - Proficiently utilizing data processing and manipulation techniques. - Building data applications using Streamlit or similar tools. - Demonstrating advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Using your problem-solving skills to work effectively in a collaborative environment. - Communicating complex technical concepts to non-technical stakeholders effectively. Qualifications required for this role include: - 4+ years of experience in machine learning, deep learning, or AI research. - Strong programming skills in Python and familiarity with relevant libraries and frameworks. - Proven experience in document detail extraction and feature engineering. - Proficiency in data processing and manipulation techniques. - Hands-on experience in building data applications using Streamlit or similar tools. - Advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Excellent problem-solving skills and the ability to work effectively in a collaborative environment. - Robust communication skills to convey complex technical concepts to non-technical stakeholders. It would be good to have the following additional skills and experiences: - Experience in the banking/financial services/industry-specific sector. - Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP. - Proven experience working with OpenAI or similar large language models (LLMs). - Certifications in Data Science, Machine Learning, or AI.