This role pays more than
95%
of similar roles. Most pay
$189,750–$246,150
— the shaded band above.
At the midpoint, this role pays about
$295k
versus about
$218k
for comparable roles.
Based on 240 similar postings.
Employer
About Cisco
Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity
Cisco currently has
197 open roles
on FindRole.
Listed pay typically runs
$167,700–$245,200
across 197 roles with salary data.
As a Machine Learning Engineering Technical Leader - CX AI, you will join the CX AI Foundations team to architect, build, and deliver enterprise-scale AI services for intelligent customer experiences. You will function as a hands-on builder, owning complex technical challenges including model selection, fine-tuning, inference optimization, agentic infrastructure, and multi-tenant API contracts across cloud and air-gapped environments. The role requires expertise in Python and modern frameworks like PyTorch or JAX to move models from research into production. You will manage high-performance inference engines such as vLLM, TensorRT-LLM, and Triton while implementing advanced techniques like quantization and speculative decoding. Key responsibilities include establishing rigorous evaluation frameworks for non-deterministic systems and managing MLOps pipelines. This role solves the challenge of providing reliable, scalable AI infrastructure across diverse compute targets in secure, production-grade environments.
Architect and deliver enterprise-scale AI services for multi-tenant platforms across cloud and on-premises environments.
Drive model selection, fine-tuning, and inference optimization using frameworks like PyTorch or JAX.
Build robust evaluation systems including judge calibration, drift detection, and regression gating as mandatory release criteria.
Design agentic infrastructure and advanced retrieval (RAG) architectures for multi-turn workflows.
Develop and package AI services for diverse compute targets, including air-gapped and resource-constrained environments.
Manage the full lifecycle of AI products from experimental incubation to production-ready engineering.
Mentor senior engineers through technical leadership and deep architectural guidance.
Ensure compliance with enterprise security standards and responsible AI governance policies.
What we're looking for
Bachelor's degree with 11+ years of related experience, or Master's degree with 7+ years of related experience.
Experience in machine learning including model development, training, adaptation, and evaluation.
Proficiency in Python and modern ML frameworks such as PyTorch or JAX.
Experience transitioning machine learning projects from research or prototype stages into production environments.
Production experience in at least one area: model serving/inference, generative AI evaluation, agentic infrastructure, or AI platform services/APIs.
Experience leading full lifecycle projects.
Track record of architecting and operating shared AI/ML inference platforms and APIs (preferred).
Expertise in high-performance inference engines, fine-tuning techniques, and building statistical evaluation frameworks for non-deterministic systems (preferred).