Applied AI Researcher: LLMs, RL & Enterprise Intelligence

Cisco; Seattle (WA); On-site; USD 198,000 - 287,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) with match

Paid parental leave

Disability coverage

Job summary

Cisco's AI Platform Team in Seattle seeks an Applied AI Researcher to turn cutting-edge research into production solutions for internal business units and customers. You will collaborate with researchers, data scientists, and engineers to translate methods into scalable, trustworthy AI deployments.

Responsibilities include designing and fine-tuning language models, building evaluation pipelines, and advancing RL and agent-simulation capabilities on NeuralFabric, with a focus on measurable impact

Qualifications

• PhD in Computer Science, ML, AI, or related field with 5+ years of applied AI/ML research or engineering.
• Experience designing, training, and fine-tuning language models for production or research.
• Proficient with Python and DL frameworks (PyTorch, TensorFlow, JAX, HF Transformers).
• Familiar with post-training methods like LoRA, QLoRA, PEFT, or RLHF.
• Proven track record leading applied AI projects from research to deployment.

Responsibilities

• Turn research methods into production-ready models on NeuralFabric.
• Define evaluation methods and model promotion gates.
• Advance RL, Auto Gym, and agent-simulation techniques.
• Collaborate with researchers and engineers to deliver impact.
• Stay current with LLMs, SLMs, and multi-modal models.

Skills

Applied AI research

Production ML

Cross-domain collaboration

Documentation and publication

Education

PhD in Computer Science / ML / AI

Tools

Python

PyTorch

TensorFlow

JAX

Hugging Face Transformers

Job description

Cisco's AI Platform Team in Seattle seeks an Applied AI Researcher to turn cutting-edge research into production solutions for internal business units and customers. You will collaborate with researchers, data scientists, and engineers to translate methods into scalable, trustworthy AI deployments.

Responsibilities include designing and fine-tuning language models, building evaluation pipelines, and advancing RL and agent-simulation capabilities on NeuralFabric, with a focus on measurable impact