GenAI Engineer

• It is 100% Onsite Position
  
• Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week
  

• Machine Learning, Deep Learning, Neural Networks, Python, Natural Language Processing, Prompt Engineering, and Data Management and Preprocessing.
  

• Design and develop generative models: This includes working with architectures like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and especially transformer-based models (like those behind LLMs).
  
• Fine-tuning and optimization: Adapting pre-trained generative models for specific tasks and datasets, optimizing their performance, efficiency, and the quality of their generated output.
  
• Prompt engineering: Crafting and refining prompts to guide generative models to produce desired outputs, often for specific applications (e.g., content creation, code generation, design).
  
• Build AI pipelines: Creating the infrastructure and workflows for data preparation, model training, deployment, and ongoing monitoring of generative AI systems.
  
• Integration: Incorporating generative AI models into existing software applications and products.
  
• Research and experimentation: Staying up to date with the latest research in generative AI and experimenting with new algorithms and techniques.
  
• Ethical considerations: Understanding and addressing potential biases, misuse, and ethical implications of generative AI.
  
• All other duties as assigned or directed.
  

Requirements

• ​Bachelor's Degree in Computer Science, Mathematics, Engineering or a related field.
  
• Masters or Doctorate degree may substitute for required experience
  
• Minimum 5 years of hands-on experience designing, developing, and implementing AI models (Generative AI experience preferred)
  
• Must be able to obtain and maintain a Public Trust. Contract requirement.
  

• Strong foundation in Machine Learning, Deep Learning, and neural networks (GANs, VAEs, Transformers, LLMs).
  
• Proficiency in programming languages, especially Python, and relevant libraries (Scikit-Learn, TensorFlow, PyTorch, Keras).
  
• Expertise in Natural Language Processing (NLP) for text and language generation.
  
• Data management, preprocessing, and feature engineering skills.
  
• Expertise with 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.
  
• Problem-solving, analytical, and critical thinking skills.
  
• Strong communication and collaboration abilities.
  
• Understanding of AI ethics and responsible AI development.
  

• Prior experience with federal or state governments IT projects.
  
• Familiarity with various LLM models available in the market
  
• Working knowledge of Retrieval Augmented Generation (RAG) to enhance LLM responses
  
• Experience integrating GenAI models and services into existing applications using APIs​