About this opportunity
Cisco Systems, Inc. lists this Lead Machine Learning Engineering, (Hybrid) opportunity in seattle, Washington. Review the employer’s description below for duties, qualifications and application requirements.
Job description
The application window is expected to close on: 09/28/2026
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 Seattle or San Jose office.
Meet the Team
The Cisco AI Research team brings together AI researchers, machine learning engineers, data engineers, and networking domain experts to build the next generation of AI-powered networking.
We work at the intersection of generative AI, large-scale data systems, and networking, developing Large Language Models (LLMs), agents, and domain-specific AI systems. Our work spans research and engineering, with a strong focus on translating advances in AI into scalable systems and real-world impact.
Your Impact
As a Lead Machine Learning Engineer, you will build and improve the data and ML systems that power our LLMs and AI models.
A major focus of this role is solving one of the most important challenges in modern AI: creating high-quality training and evaluation data at scale. You will design and build scalable data pipelines, improve human data labeling workflows, create synthetic datasets, and develop automated approaches for continuously measuring and improving dataset quality.
This is a hands-on technical role at the intersection of machine learning engineering and data engineering. You will work closely with researchers, engineers, and domain experts to determine what data our models need, how to create it efficiently, and how to measure its impact on model performance.
Design, build, and maintain robust, scalable data pipelines that support the full lifecycle of ML and LLM development, from initial data ingestion to production-ready model deployment.
Architect and manage human-in-the-loop labeling workflows, including task generation, quality control, and feedback integration to ensure high-fidelity training data
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Worksite address
seattle, WA, 98127, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.