Position Overview: - Design and Develop Generative Models: Work with architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models (like those used in Large Language Models, or LLMs). - Fine-Tuning and Optimization: Adapt pre-trained generative models for specific tasks and datasets, focusing on optimizing their performance, efficiency, and the quality of generated outputs. - Prompt Engineering: Craft and refine prompts to guide generative models in producing desired outputs for specific applications, including content creation, code generation, and design. - Build AI Pipelines: Create the infrastructure and workflows for data preparation, model training, deployment, and ongoing monitoring of generative AI systems. - Integration: Incorporate generative AI models into existing software applications and products. - Research and Experimentation: Stay updated with the latest research in generative AI and experiment with new algorithms and techniques. - Ethical Considerations: Understand and address potential biases, misuse, and moral implications associated with generative AI. - Other Duties as Assigned: Perform any other tasks as directed. Skills Requirements: Basic Qualifications: - Bachelor’s Degree in Computer Science, Mathematics, Engineering, or a related field. A master’s or doctoral degree may substitute for required experience. - Minimum of 5 years of hands-on experience in designing, developing, and implementing AI models (experience in Generative AI is preferred). - Must be able to obtain and maintain a Public Trust—contract requirement. - The selected candidate must be willing to work on-site in Woodlawn, MD, five days a week. Required Skills: - Strong foundation in Machine Learning, Deep Learning, and neural networks (including GANs, VAEs, Transformers, and LLMs). - Proficiency in programming languages, particularly Python, along with relevant libraries (such as Scikit-Learn, TensorFlow, PyTorch, Keras). - Expertise in Natural Language Processing (NLP) for text and language generation. - Skills in data management, preprocessing, and feature engineering. - Proficiency in prompt engineering techniques for guiding AI models. - Experience with cloud-based AI platforms (AWS, Azure). - Knowledge of software development best practices, including CI/CD pipelines, version control, and testing. - Strong problem-solving, analytical, and critical thinking capabilities. - Excellent communication and collaboration skills. - Understanding of AI ethics and responsible AI development. Desired Skills: - Prior experience with federal or state government IT projects. - Familiarity with various LLM models available in the market. - Working knowledge of Retrieval Augmented Generation (RAG) to enhance LLM responses. - Experience integrating generative AI models and services into existing applications using APIs. Education: - Bachelor's Degree in Computer Science, Mathematics, Engineering, or a related field. - Must be able to obtain and maintain a Public Trust—contract requirement. Job Types: Full-time, Contract Pay: Up to $79.00 per hour Education: Bachelor's (Required) Experience: designing, developing, and implementing AI models : 7 years (Required) Generative AI : 5 years (Required) Machine Learning: 7 years (Required) generative AI models : 7 years (Required) neural networks : 7 years (Required) GANs, VAEs, Transformers, and LLMs: 7 years (Required) Python: 7 years (Required) Scikit-Learn, TensorFlow, PyTorch, Keras: 7 years (Required) Natural Language Processing (NLP) : 7 years (Required) cloud-based AI platforms (AWS, Azure): 7 years (Required) federal or state government IT projects: 5 years (Required) Security clearance: Confidential (Required) Ability to Commute: Windsor Mill, MD 21244 (Required) Work Location: In person