AI Operations Engineering Technical Leader
Meet the Team
The Cisco AI Software & Platform Group incubates and delivers Generative AI based solutions to reinvent Cisco's existing Products and how customers interact with them. Our Group is also introducing new offerings that help customers roll out Generative AI at scale while doing so responsibly. Ultimately, we are doing so through internal platforms that unlock the benefits of this technology for Cisco teams and partners across our Security, Enterprise Networking, Collaboration and Splunk portfolios.
Your Impact
Cisco is looking for a highly experienced and innovative ML Operations Engineer to join
our global DevOps team. In this critical role, you will drive the production readiness, deployment, and maintenance of scalable machine learning systems. You will work closely with cross-functional team of data scientists, software development engineers, information security professionals, and DevOps engineers on creating secure and resilient ML pipelines.
Key Responsibilities
- Design, build, and manage robust ML pipelines for training, validation, and deployment
- Build and maintain scalable infrastructure for ML experiments and inference in multiple public cloud
- Implement CI/CD for ML systems ensuring reproducibility and traceability
- Advocate automation in every layer of the infrastructure stack using Infrastructure as Code (IaC) principles and tools such as Terraform, Helm, and GitOps frameworks.
- Monitor models in production for performance degradation, drift, and fairness
- Participate in on-call rotation for ML Operations
- Work closely with data scientists, engineers, and product managers to understand requirements and integrate models into applications
Minimum Qualifications
- Bachelors degree in Comp Science, Engineering (or related field /industry) + 8 years of DevOps experience, Masters + 6 years of related experience, or PhD + 3 years of related experience.
- Strong understanding of CI/CD pipelines and automation tools.
- Knowledge of cloud platforms (AWS, Azure, GCP)
- Proficiency in Python and familiarity with ML libraries (e.g., Scikit-learn, PyTorch, TensorFlow, etc.)
- Strong understanding of ML lifecycle management and model versioning
Preferred Qualifications:
- Experience deploying large language models (LLMs) or generative AI systems
- Familiarity with feature stores, vector databases, or data observability platforms
- Excellent communication, collaboration, and mentoring skills.
- Deep expertise in CI/CD tooling and practices, including hands-on experience with systems like Jenkins, GitLab, ArgoCD, or similar.
- Strong proficiency in Kubernetes, Docker, and cloud-native patterns in AWS, Azure, or GCP.
#WeAreCisco
#WeAreCisco where every individual brings their unique skills and perspectives together to pursue our purpose of powering an inclusive future for all.
Our passion is connection—we celebrate our employees’ diverse set of backgrounds and focus on unlocking potential. Cisconians often experience one company, many careers where learning and development are encouraged and supported at every stage. Our technology, tools, and culture pioneered hybrid work trends, allowing all to not only give their best, but be their best.
We understand our outstanding opportunity to bring communities together and at the heart of that is our people. One-third of Cisconians collaborate in our 30 employee resource organizations, called Inclusive Communities, to connect, foster belonging, learn to be informed allies, and make a difference. Dedicated paid time off to volunteer—80 hours each year—allows us to give back to causes we are passionate about, and nearly 86% do!
Our purpose, driven by our people, is what makes us the worldwide leader in technology that powers the internet. Helping our customers reimagine their applications, secure their enterprise, transform their infrastructure, and meet their sustainability goals is what we do best. We ensure that every step we take is a step towards a more inclusive future for all. Take your next step and be you, with us!
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