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Job Summary:
The Software Engineering Institute at Carnegie Mellon University is seeking an AI Engineer to conduct research in applied artificial intelligence and develop robust AI solutions for the defense and national security sectors. The role involves designing and deploying AI models and collaborating with interdisciplinary teams to operationalize AI technologies for mission capabilities.
Responsibilities:
• Design, develop, and fine‑tune a variety of AI models.
• Design autonomous agents and multi‑step pipelines using LangChain, ReAct, tool‑calling, or custom orchestration; employ the Model Context protocol to manage stateful interactions.
• Build Retrieval‑Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications.
• Implement end‑to‑end data pipelines, ETL processes, and back‑end services (Python, C/C++, Java) that feed data to models.
• Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning; maintain model registries, monitoring, and version control of context protocols.
• Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments.
• Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation.
• Stay current with emerging LLM architectures, agentic paradigms, PEFT/LoRA methods, and AI‑safety techniques; translate new research into operational capabilities.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field with at least eight (8) years of relevant experience, or a MS degree in the same with at least five (5) years of relevant experience.
• You will be subject to a background investigation and must be able to obtain and maintain an active Department of War (DoW) security clearance.
• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.
• Proficiency in Python and at least one compiled language (C/C++ or Java); experience with REST/GraphQL APIs and containerization.
• Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics.
• Hands‑on experience fine‑tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools.
• Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers).
• Experience applying PEFT/LoRA methods (e.g., LoRA, adapters) to large models.
• Understanding of Model Context protocols for managing model state across multi‑turn interactions.
• Experience building evaluation frameworks, benchmarks, or data quality pipelines.
• Experience with TensorFlow, PyTorch, or JAX; knowledge of data‑pipeline tools (Airflow, Prefect, Ray) is a plus.
• Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model‑registry concepts) is desirable.
Preferred:
• Deploying LLM APIs (FastAPI, gRPC) at scale, handling latency and load balancing.
• Building multi‑tool agents, planner‑executor loops, or tool‑calling pipelines for complex decision‑making.
• Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research.
• Utilizing GPU/TPU resources, mixed‑precision training, and distributed training frameworks such as DeepSpeed or ZeRO.
• Prior work on defense, intelligence, or government‑focused AI projects and familiarity with DoW acquisition or compliance processes.
• Contributing to open‑source AI and ML libraries, agentic frameworks, or context‑protocol implementations.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.