Machine Learning Engineer

Candidates must have an active secret clearance or higher. We are seeking an experienced Staff or Senior Machine Learning Engineer with deep expertise in Large Language Models (LLMs), Mixture of Experts (MoEs), and Natural Language Processing (NLP). The ideal candidate will have a proven track record of developing, fine-tuning, and deploying advanced AI models at production scale. You'll collaborate closely with research and engineering teams to design, build, and optimize models that work with both structured and unstructured language data. This role spans cutting-edge research, hands-on model development, and MLOps-an opportunity to put your name on meaningful, real-world impact. Key Responsibilities Lead the design, development, and optimization of Large Language Models, Mixture of Experts models, and NLP systems for tasks including language understanding and generation. Extend existing LLM frameworks and libraries, incorporating the latest research in language models and transformer architectures. Preprocess and prepare text datasets for training, including tokenization, feature extraction, and data pipeline development. Implement MLOps best practices for deploying scalable, production-level models on cloud platforms. Collaborate with cross-functional teams to integrate ML models into the broader platform. Conduct cutting-edge research in machine learning, with a focus on improving model performance, efficiency, and scalability. Stay current with the latest advancements in AI and ML and apply that knowledge to improve models and methodologies. Mentor junior engineers and contribute to knowledge sharing and team best practices. Required Qualifications Bachelor's degree (Master's or Ph.D. preferred) in Computer Science, Machine Learning, or a related field. 5+ years of experience in machine learning, with specific expertise in LLMs, NLP, and/or Mixture of Experts architectures. Expertise in transformer architectures (e.g., GPT, BERT) and text preprocessing / feature engineering. Strong programming skills in Python and ML frameworks such as TensorFlow and/or PyTorch. Proficiency with NLP libraries and tooling (e.g., Hugging Face Transformers). Experience with MLOps tools and workflows (MLFlow, Kubeflow, or similar). Demonstrated ability to lead complex projects and work collaboratively in a team environment. Excellent problem-solving skills and a passion for innovation. Strong communication skills and a desire for continuous learning. Preferred Skills Experience with cloud computing services (AWS, Azure, GCP). Knowledge of Big Data technologies (Hadoop, Spark). Familiarity with containerization and orchestration technologies (Docker, Kubernetes). Proven track record of innovation through publications, patents, or industry contributions. Publications or presentations at recognized machine learning journals or conferences.