Staff Applied Scientist

Cisco Systems, Inc.•San Jose, CA

35d

About The Position

Splunk, a Cisco company, is building a safer, more resilient digital world with an end-to-end, full-stack platform designed for hybrid, multi-cloud environments. Join the Code Generation group, where we work on automating the code generation process using GenAI techniques. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco's global engineering capabilities. Our work spans networking, security, observability, and customer experience, designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You'll be part of a culture that values technical excellence, impact-driven innovation, and cross-functional collaboration, all within a flexible, growth-oriented environment. 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.

Requirements

PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field with 2+ years of industry or post-doctoral research experience;
or a Master's degree with 6+ years of relevant applied ML or research experience.
Demonstrated expertise in at least one of the following:
Large language models for program synthesis, code understanding, or formal languages
Multi-step planning or agentic AI for developer workflows
Strong programming proficiency in Python and hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
Experience translating research prototypes into production systems, including deployment, optimization, and performance evaluation.
Working knowledge of experimental design, benchmarking, reproducibility, evaluation metrics, and scientific documentation.

Nice To Haves

LLMs for Code Generation - Experience training, fine-tuning, or adapting models such as Code-LLaMA, CodeT5, StarCoder, or GPT-based code models for program synthesis, bug fixing, refactoring, test generation, static/dynamic analysis, or domain-specific languages (DSLs).
Domain-Specialized Modeling - Experience building models for structured languages such as SQL, DSLs, configuration languages, or proprietary query/automation languages.
Agentic AI & Tool Use - Experience developing systems where models plan, call tools/APIs, self-correct, or execute code iteratively to improve output quality.
Structured Reasoning & Planning - Familiarity with techniques such as chain-of-thought prompting, constrained decoding, self-debugging, or reinforcement learning for code-centric tasks.
Large-Scale Training & Optimization - Experience with distributed training or inference optimization (quantization, LoRA, batching, caching) to improve latency, cost, and accuracy trade-offs.
MLOps & Continuous Evaluation - Exposure to automated retraining, dataset versioning/curation, evaluation harnesses, and reliability monitoring for ML models in production.
Research Visibility - Publications in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, ACL, AAAI, KDD) and/or meaningful contributions to the LLM/code-gen research community (open-source, tools, datasets, or benchmarks).

Responsibilities

Design, build, and deploy advanced AI models for intelligent code generation, contributing across model architecture, experimentation, evaluation, and integration into production systems.
Push the boundaries of agentic GenAI by developing models that not only generate code but also reason, plan, self-correct, and interact with tools, APIs, and execution environments to improve reliability and usability.
Enhance code-generation capabilities for DSLs and structured languages, helping shape the next generation of developer experiences powered by LLMs in both interactive and automated workflows.
Optimize training and inference workflows through efficient data pipelines, distributed training strategies, and model-level performance improvements to ensure low latency, high accuracy, and cost-effectiveness.
Partner closely with engineering and product teams to ensure research outcomes are aligned with customer needs and translate into scalable, high-impact product features.
Contribute to the scientific culture of the team, sharing best practices in rigorous experimentation, reproducibility, evaluation design, and documentation.
Participate in long-term AI innovation by identifying emerging opportunities, proposing new directions, and shaping roadmap priorities in collaboration with research and engineering leaders.

Benefits

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.
Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
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 of unused sick time carried forward from one calendar year to 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
Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.