Machine Learning Engineering Technical Leader

Cisco

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Seattle, WA
Salary
$234,400–$296,600 / yr
Employment
Full-time
Posted
46 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $223k
This role $266k
$165k $311k
below market most similar roles pay here above market

This role pays more than 85% of similar roles. Most pay $195,823–$250,875 — the blue band above. At the midpoint, this role pays about $266k versus about $223k 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 296 open roles on FindRole.

Listed pay typically runs $167,700–$245,200 across 228 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineering Technical Leader

JOB TITLE: Machine Learning Engineering Technical Leader As a Senior Staff Applied Scientist 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 research, including model design, evaluation, and production rollout for agentic GenAI. Your daily work involves defining scientific roadmaps for models that reason, plan, and self-correct while advancing DSL-aware code synthesis. You will drive the efficiency of distributed training and inference pipelines to balance performance and cost. Key technologies include Python, PyTorch, and TensorFlow, with specific experience in LLMs like Code-LLaMA, CodeT5, and StarCoder. You will solve complex problems in program synthesis, multi-step planning, and MLOps to translate research prototypes into high-impact customer capabilities across networking, security, and observability.

What you'll do

  • Own the full lifecycle of research and deployment for next-generation AI systems for intelligent code generation.
  • Define the scientific roadmap for agentic GenAI models that can reason, plan, and self-correct.
  • Advance the state of the art in DSL-aware code synthesis for interactive and automated developer workflows.
  • Drive the efficiency and scalability of distributed training and inference pipelines to balance performance and cost.
  • Translate research prototypes into production systems, including model deployment, optimization, and evaluation.
  • Mentor a high-performing research organization to foster a culture of scientific rigor and delivery excellence.
  • Shape long-term AI strategy and influence architectural decisions and technical investments across the GenAI organization.

What we're looking for

  • PhD in Computer Science, Machine Learning, AI, or a related field with 5+ years of post-doctoral or industry experience.
  • Master’s degree in a related field with 10+ years of industry experience.
  • 3+ years of experience developing Large Language Models (LLMs) for program synthesis or formal languages.
  • 2+ years of experience in multi-step planning or agentic AI for developer workflows.
  • 3+ years of experience with Python and deep learning frameworks such as PyTorch or TensorFlow.
  • 3+ years of experience translating research prototypes into production systems, including model deployment, optimization, and evaluation.
  • Strong foundation in experimental design, benchmarking, reproducibility, evaluation metrics, and scientific documentation (preferred).
  • Publications in premier AI/ML venues or recognized contributions in the code-gen/LLM community (preferred).

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