Machine Learning Engineer

Application window is expected to close on: 07/31/2026. Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received. This is a hybrid role based out of Cisco's San Jose or Seattle office. Meet the Team The Cisco AI Research team is composed of AI research scientists, data scientists, and network engineers with deep subject matter expertise. This diverse group collaborates on both foundational and applied research projects, driven by the challenge of connecting people and devices at a global scale. The team is newly formed and dynamic, blending AI and networking domain experts who work closely with engineers, product managers, and strategists experienced in AI and distributed systems. Members have the opportunity to shape the culture and direction of this growing team. Your Impact We are seeking a Machine Learning Engineer to build dynamic troubleshooting agents that don’t just monitor networks—they understand them. Our team is solving for the massive complexity of unstructured production log data, optimizing hardware utilization for data collection, and automating the creation of synthetic datasets that push the boundaries of what LLMs can achieve in network configuration and remediation. You won’t just be maintaining pipelines—you will be architecting the data infrastructure that allows our models to reason through real-world network failures in real-time. Design and scale automated pipelines that transform raw, high-velocity production logs into high-quality insights. Develop systems that generate synthetic data, enabling our models to learn from edge cases that rarely occur in the wild. Solve network complexity problems by tackling the unique challenges of time and network state dependencies to improve the accuracy of our agents. Optimize at scale through efficient data collection and hardware utilization, ensuring our ML infrastructure remains performant as our agent capabilities expand. Help shape the future of Network AI by collaborating directly with researchers to define the next generation of AI‑driven network management for Cisco network products such as Meraki, ThousandEyes, Catalyst Center and Nexus. Minimum Qualifications Bachelor's degree in STEM and 5+ years of relevant experience, or Master's degree in STEM and 3+ years of relevant experience, or PhD in STEM and 0+ years of relevant experience or equivalent related work experience. 5+ years of experience in data engineering, machine learning engineering, or related roles. Data pipeline experience, designing and scaling data pipelines for unstructured or semi-structured data, including ingestion, cleansing, and auditing. ML infrastructure experience working with ML data workflows, including dataset creation, labeling, and evaluation. Experience with Python and data processing frameworks (e.g., Spark, Beam, Ray). Experience with ML systems and tools, such as training pipelines and model evaluation frameworks. Preferred Qualifications Experience with human‑in‑the‑loop ML systems, active learning, weak supervision or self‑evolving agents. Exposure to large language models, computer vision, or speech datasets. Experience building internal tools or platforms used by annotation or operations teams. #J-18808-Ljbffr