Sr. Machine Learning Engineer (US Security Clearance)

Special Notice:This position is not contingent upon awarding of a project or funding source. This is direct, immediate, full-time employment with webAI. This position is hybrid; candidates must be based in Austin TX, Washington DC or willing to relocate. An active US Security Clearance is required.About the Role:We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments.You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments.Responsibilities:Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems.Productionize AI models from research prototypes into scalable, deployable systems used in real world applications.Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific acceleration.Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval.Work with multi-modal AI systems across computer vision, audio, and natural language domains.Optimize model execution for distributed and resource constrained environments, ensuring reliability under variable connectivity conditions.Required:Active US Security clearance4+ years of experience in applied AI, ML engineering, or production AI systems.Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.Proven experience deploying AI models across cloud, edge, and mobile hardware environments.Expertise in model compression and optimization (quantization, pruning, distillation).Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone).Familiarity with multi-modal models and synthetic data generation methods.Strong algorithmic and problem solving skills, especially in distributed or constrained compute environments.Preferred Skills:Experience with edge AI, federated learning, or offline inference systems.Understanding of AI governance and compliance frameworks relevant to public sector deployments.Experience integrating models into large scale distributed systems or microservice architectures.Excellent communication and technical documentation skills for collaboration across multi disciplinary teams.Strong understanding of GPU computing, CUDA, and performance profiling.Benefits:Competitive salaryComprehensive health, dental, and vision benefits packageEquity options401(k) match (U.S.-based employees only)$200/month Health & Wellness stipendContinuing Education support$500/year Function Health subscription (U.S.-based employees only)Free parking for in-office employeesFlexible Time Off (FTO)Parental leave for eligible employeesSupplemental life insurancewebAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.