Full-Time

Senior Manager

Machine Learning Engineer, ML Ops

Posted on 9/17/2025

Cisco

Cisco

10,001+ employees

Networking hardware, security software, collaboration services

No salary listed

San Jose, CA, USA

In Person

Category
AI & Machine Learning (2)
,
Required Skills
LLM
Kubernetes
Pinecone
Microsoft Azure
Python
Pytorch
Machine Learning
AWS
LangChain
Google Cloud Platform
Requirements
  • 8+ years of software engineering experience, with 3+ years in engineering management or technical leadership roles.
  • Proven track record of shipping production-grade ML/LLM systems.
  • Strong understanding of LLMs, fine-tuning, prompt engineering, vector databases (e.g., Pinecone, Weaviate, FAISS), and RAG patterns.
  • Experience with cloud-native architectures (AWS, GCP, or Azure) and container orchestration (Kubernetes).
  • Proficiency in Python and familiarity with AI/ML frameworks such as PyTorch, Transformers, LangChain, or similar.
Responsibilities
  • Lead and grow a high-performing engineering team focused on LLM applications and infrastructure.
  • Foster a culture of engineering excellence, continuous learning, and innovation.
  • Drive team performance through mentoring, goal-setting, and technical guidance.
  • Design and oversee scalable LLMOps pipelines including fine-tuning, evaluation, deployment, monitoring, and optimization of large language models.
  • Work closely with ML researchers to transition experimental models into production.
  • Manage model lifecycle tooling (e.g., LangChain, MLflow, Weights & Biases, Hugging Face, Ray).
  • Oversee the design and implementation of RAG pipelines including vector database management, chunking strategies, embedding selection, retrieval tuning, and relevance evaluation.
  • Optimize latency, accuracy, and context window handling for high-traffic LLM services.
  • Own architectural decisions for high-availability, low-latency systems powering generative AI applications.
  • Collaborate with infrastructure and DevOps teams on scaling inference workloads (e.g., with GPU clusters, model quantization, caching, and sharding).
  • Work with product, design, and data science to define requirements, translate business needs into engineering tasks, and prioritize effectively.
  • Maintain high communication standards across teams, ensuring alignment and transparency.
  • Champion model observability, incident response, prompt versioning, and feedback loops.
  • Ensure responsible AI practices and data governance are followed.
Desired Qualifications
  • Experience managing or working with multi-modal or multi-agent systems.
  • Exposure to regulatory or compliance frameworks for ML systems (e.g., GDPR, SOC 2).
  • Hands-on experience with observability and evaluation tools for LLMs.

Cisco designs and sells networking hardware, software, and services that help organizations connect, protect, and manage data. Its products include networking gear, security solutions, cloud services, and collaboration tools like Webex to support hybrid work. Cisco differentiates itself with a broad, integrated stack—routing and switching, security, cloud, and collaboration—that works together at scale. Its goal is to help customers securely connect people, devices, and applications, enabling reliable communication and digital transformation across enterprises of all sizes.

Company Size

10,001+

Company Stage

IPO

Headquarters

San Jose, California

Founded

1984

Simplify Jobs

Simplify's Take

What believers are saying

  • Cisco reported $2.1 billion in AI infrastructure orders in fiscal Q2 2026.
  • Cloud Control can raise software and services attach rates across installed networks.
  • Workday Agent Passport positions Cisco as a validation layer for enterprise AI governance.

What critics are saying

  • Layoffs and restructuring can slow execution and weaken customer support during transition.
  • Cloud Control faces entrenched rivals and competing NVIDIA-backed enterprise AI architectures.
  • Quantum-safe and Live Protect adoption can lag, delaying revenue and pressuring returns.

What makes Cisco unique

  • Cloud Control unifies networking, observability, and security in one AI platform.
  • Cisco combines Live Protect, quantum-safe security, and Splunk automation for defense depth.
  • Secure AI Factory with NVIDIA anchors Cisco in enterprise AI infrastructure.

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Benefits

Paid Vacation

Hybrid Work Options

Flexible Work Hours

Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

1%

2 year growth

1%
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