This role pays more than
84%
of similar roles. Most pay
$189,750–$254,750
— the shaded band above.
At the midpoint, this role pays about
$266k
versus about
$222k
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 within the Code Generation group, you will lead the research and deployment of next-generation AI systems for intelligent code generation. You will own the full lifecycle of these systems, including model design, evaluation, and production rollout while defining the scientific roadmap for agentic GenAI to enable models that reason, plan, and self-correct. Your work focuses on advancing DSL-aware code synthesis and improving the efficiency of distributed training and inference pipelines. To succeed, you must possess expertise in Python, PyTorch or TensorFlow, and experience with Large Language Models like Code-LLaMA or StarCoder. You will solve complex problems involving program synthesis, refactoring, and unit test generation while managing MLOps tasks such as dataset curation and model health monitoring to enhance developer experiences across interactive and automation-driven workflows.
Own the full lifecycle of research and deployment for next-generation AI systems for intelligent code generation.
Define the scientific roadmap for agentic GenAI to enable models that reason, plan, and self-correct.
Advance state-of-the-art techniques in DSL-aware code synthesis for automated and interactive developer workflows.
Optimize distributed training and inference pipelines to balance performance, latency, and cost while maintaining accuracy.
Translate research prototypes into production systems by managing model deployment, optimization, and evaluation.
Mentor a high-performing research organization to foster scientific rigor and delivery excellence.
Shape long-term AI strategy and influence architectural decisions across the GenAI organization.
What we're looking for
A PhD in Computer Science, Machine Learning, AI, or a related field with 5+ years of research experience is required; or a Master's degree with 10+ years of research experience.
At least 3 years of experience developing Large Language Models (LLMs) for program synthesis or formal languages is required.
At least 2 years of experience in multi-step planning or agentic AI for developer workflows is required.
At least 3 years of experience with Python and deep learning frameworks like PyTorch or TensorFlow is required.
At least 3 years of experience translating research prototypes into production systems, including model deployment, optimization, and evaluation, is required.
Experience with training, fine-tuning, or adapting models for program synthesis, refactoring, or domain-specific languages (preferred).
Experience building generative models for structured languages like SQL or configuration languages (preferred).
Experience with distributed training, efficient inference techniques, and MLOps practices such as dataset curation and model monitoring (preferred).