This role pays more than
52%
of similar roles. Most pay
$144,350–$177,250
— the shaded band above.
At the midpoint, this role pays about
$152k
versus about
$161k
for comparable roles.
Based on 240 similar postings.
Employer
About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has
586 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 577 roles with salary data.
Software Engineering II and Senior Software Engineer (CoreAI - Post Training) will join the CoreAI team to build and evolve distributed services that underpin massive training runs. The role involves improving iteration loops for researchers and engineers while applying advanced performance optimization techniques to impact product quality and operational excellence. Responsibilities include developing expertise in ML systems, AI infrastructure, and compute orchestration while ensuring system architecture meets scalability, resiliency, and cost requirements. Candidates will work with technologies including C, C++, C#, Python, or Java, alongside specialized tools like vLLM, SGLang, VERL, Slime, and Ray. The role focuses on the technical challenges of reinforcement learning, post-training, and container workloads. Key domain expertise includes GPU computing, distributed training infrastructure, and optimizing models and inference systems rather than just utilizing existing technologies to solve complex AI production problems.
What does a Software Engineer earn?
Median $197500 from 2229 postings across 139 companies.
Build and evolve distributed services that support massive training runs and improve iteration loops for researchers.
Apply advanced performance optimization techniques to impact product quality and operational excellence.
Develop high-quality, maintainable, and secure code while utilizing AI tools throughout the software development lifecycle.
Design and evaluate architecture options to ensure system scalability, resiliency, and cost-effectiveness.
Implement security best practices, including "security as code" and automated deployment gates for product features.
Manage live site operations by responding to incidents, performing root cause analysis, and improving telemetry.
Execute project plans by breaking down complex work items into manageable tasks with accurate estimations.
Optimize training and inference systems using technologies like vLLM, SGLang, and Ray.
What we're looking for
Bachelor's Degree in Computer Science or related technical field and 2+ years of engineering experience in C, C++, C#, Python, or Java (or equivalent).
Experience in cloud software development.
Knowledge of containers, GPU computing, and distributed training infrastructure.
Ability to modify, optimize, or improve models and training/inference systems rather than just using the technologies.
Experience in reinforcement learning, post-training, and container workloads (preferred).
Experience with inference technologies such as vLLM, SGLang, and disaggregated inference (preferred).
Experience with training and orchestration technologies such as VERL, Slime, and Ray (preferred).
Python
Java
Go
C++
C
JavaScript
Azure
AWS
GCP
Distributed Systems
CI/CD
Kusto
Azure Data Explorer
Spark
Telemetry
Monitoring
Security Engineering
AI/ML