AI/ML Technical Leader - Language Model Inference & AI Ops

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 in San Jose, CA. Must be able to work on site 3 days per week.

Meet the Team

Join Cisco's CX AI Incubation Team as an AI Operations Technical Leader and help productionize LLM/SLM capabilities for Intelligent Customer Experiences, across cloud and on-prem environments. In Cisco CX, you will build andoperatescalable AI systems that move from prototype to production,poweringdelivery intelligence, network automation, infrastructure testing, and intelligence on edge.

You will collaborate with product and engineering teams to deploy reliable, secure, and observable AI services,optimizinginference performance from CPU and small GPUs to large multi-GPU servers, including air-gapped and customer-managed deployments.

You'll work on cutting-edge inference optimization - speculative decoding, continuous batching, quantization, and KV-cache strategies to deliver cost-effective, low-latency AI across cloud, on-prem, and air-gapped environments.

Your Impact

Join Cisco's Customer Experience (CX) AI Incubation team to build and run production-grade AI platforms and services that transform customer engagement and operational efficiency. You will focus on end-to-end AI DevOps for LLMs/SLMs, including on-prem inference packaging, runtime optimization, deployment automation, and model/service observability. This role requires strong software engineering, hands-on GPU inference experience, anda track recordof operationalizing models at scale.

WhatYou'llDo

ProductionizeLLM/SLM-powered features by building robust model-serving anddeploymentpipelines (cloud + on-prem) with clear SLAs, monitoring, and rollback strategies.Optimizeinference performance across CPUs and small GPUs using techniques such as speculative decoding, continuous batching, paged attention, KV-cache reuse, and low-bit quantization (F8/INT4) for cost and latency wins. Package and integrate on-prem inference stacks (VM/containers) with customer environments, including secure configuration, versioning, and upgrade-safe deployments.

Design scalable serving architectures for generative AI (multi-tenant, secure, cost-aware), including tensor/pipeline parallelism, disaggregated prefill/decode, capacity planning, and performance benchmarking.Build automated CI/CD for models and prompts: evaluation gates, regression testing, artifact management, and reproducible releases. Implement model and service observability: latency/throughput metrics, quality drift signals, safety checks, and incident triage workflows.

Support training and fine-tuning workflows for LLMs/SLMs, including data curation, experiment tracking, and packaging models for production.Partner with product and engineering to integrate AI services into applications, ensuring reliability, security, and responsible AI behavior.Evaluate and adopt emerging inference techniques and runtimes; drive build-vs-adopt decisions across vLLM, TensorRT-LLM, SGLang, llama.cpp, and similar engines based on workload characteristics.

Minimum Qualifications

• Bachelor's degreewith9+ years ofrelatedexperience, orMastersdegree with7+ years ofrelatedexperience.

• Experience in Python, Java or C++, and building production services for ML/AI workloads.

• Experience withPyTorch/TensorFlow and tooling across the ML lifecycle (data pipelines, training, evaluation, deployment).

• Experience deploying and operating NLP/Generative AI systems in production, including performance tuning and reliability practices.

• Experience working in cross-functional teams, delivering in fast-paced environments, and communicating technical concepts clearly.

Preferred Qualifications

~Inference & Serving

• Proven experience productionizing LLMs/SLMs with GPU-backed inference and runtime optimization.

• Hands-on experience with inference engines - vLLM, TensorRT-LLM, Triton, SGLang, llama.cpp and GPU profiling (Nsight, PyTorch profiler).
• Working knowledge of speculative/assisted decoding, continuous batching, paged/flash attention, KV-cache management, and structured/constrained decoding (guided JSON, grammar-based).
• Experience with quantization techniques (GPTQ, AWQ, SmoothQuant, FP8, INT4) and accuracy/perf tradeoffs.
• Familiarity with multi-GPU parallelism (tensor, pipeline, expert) and disaggregated serving patterns.

~Model Adaptation

• Experience with PEFT (LoRA, QLoRA), distillation, and SLM specialization for domain-specific deployments.
• Familiarity with LLM-evaluation (LLM-as-a-judge, golden sets, drift detection, regression gates).

~On-Prem, Edge & Infra

• Hands-on experience with on-prem deployment patterns (air-gapped, customer-managed), packaging, integration, upgrade strategy.
• Exposure to edge/resource-constrained inference (CPU, NPU, small GPU; runtimes like llama.cpp, ONNX Runtime, OpenVINO, MLC).
• Experience with AI infra and MLOps tooling such as K8s, CI/CD, model registry, experiment tracking, observability.

~Communication

• Strong written and verbal communication; ability to drive design reviews and produce clear technical documentation.

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco's policies:

• 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees

• 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco

• Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees

• Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)

• 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours ofunused sick timecarried forwardfrom one calendar yearto the next

• Additional paid time away may be requested to deal with critical or emergency issues for family members

• Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

• .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

• 1.5% of incentive target for each 1% of attainment between 50% and 75%;

• 1% of incentive target for each 1% of attainment between 75% and 100%; and

• Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

Non-Metro New York state & Washington state:

* For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.