Cisco
Machine Learning Engineering Technical Leader
$198K–$323K
Milpitas, California, US +1 · Hybrid · Full-time · Posted Oct 23, 2026
- Location
- Milpitas, California, US
San Francisco, California, US - Experience
- BA/BS: 8+ years; MS: 6+ years; PhD: 3+ years of relevant experience.
- Education
- BA/BS, MS, or PhD in Computer Science, Machine Learning, or a related quantitative field.
About the job
Leads the strategy and engineering of trustworthy evaluation systems for Cisco’s agentic AI products, from architecture through production monitoring and validated improvements.
What you'll do
- Set the evaluation roadmap and build layered systems combining automated checks, LLM judges, and expert human review.
- Monitor production performance, run simulation and testing, and turn evaluation failures into validated fixes.
- Set shared standards across teams, mentor engineers, and represent the domain to senior leadership.
What they ask for
- BA/BS with 8+ years, MS with 6+ years, or PhD with 3+ years of relevant experience in Computer Science, Machine Learning, or a related quantitative field.
- Experience taking machine learning or LLM-based systems into production and owning them operationally.
- Experience with Python and modern deep learning frameworks such as PyTorch or TensorFlow.
- Experience designing ML or LLM evaluation, measurement, or quality systems, and setting technical direction across teams through influence.
Nice to have
- Practical experience designing and calibrating LLM judges against human experts, or evaluating agentic systems.
- Experience in production monitoring, simulation, synthetic data, CI/CD evaluation, networking or observability, cost-aware inference, or technical community contributions.
Pay
$216,300.00 to $280,800.00 USD base salary; $216,300.00 - $322,900.00 USD base salary; $197,500.00 - $287,300.00 USD base salary
Tools
Python, PyTorch, TensorFlow
AI focus
Agentic AI quality evaluation, including LLM-as-judge systems, human-in-the-loop calibration, production scoring, simulation, and validated fixes.
Model-written summary · the original posting is authoritative