below marketmost similar roles pay hereabove market
This role pays more than
63%
of similar roles. Most pay
$186,331–$254,750
— the blue band above.
At the midpoint, this role pays about
$231k
versus about
$221k
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
694 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 651 roles with salary data.
Member of Technical Staff, Microsoft Robotics joins the Discovery and Quantum division to lead the technical direction of the Microsoft Robotics platform. This Principal level role involves owning the multi-year technical architecture for a platform that integrates humans, robots, and AI agents through robotics AI models and physically grounded agentic workflows. You will make foundational design decisions for robotics software, AI models, and cloud and edge components while balancing latency, throughput, and reliability. Key responsibilities include leading evaluation strategies for autonomy, safety, and task performance across simulation and field environments. Required skills include proficiency in C, C++, C#, Java, JavaScript, or Python. Experience with ROS, ROS2, Nav2, MoveIt, Isaac Sim, MuJoCo, Drake, and Gazebo is preferred to solve complex integration problems in embodied AI.
Own the multi-year technical architecture for the Microsoft Robotics platform to ensure coherence as it scales.
Make foundational design decisions for integrating robotics software, AI models, and cloud and edge components.
Architect systems that balance latency, throughput, compute efficiency, reliability, and cost across cloud and edge environments.
Lead the evaluation and validation strategy to establish benchmarks for autonomy, safety, and task performance.
Resolve complex cross-stack technical problems and integration failure modes where AI models meet production robots.
Integrate classical robotics engineering with modern AI capabilities into a common, production-grade platform.
Establish engineering standards and lead technical reviews to improve the quality and testability of systems.
Build technical consensus across internal teams and external partners to align on a single platform strategy.
What we're looking for
Bachelor's Degree in Computer Science or related technical field and 8+ years of technical engineering experience with coding in languages like C, C++, C#, Java, JavaScript, or Python.
Ability to pass Microsoft, customer, and/or government security screenings, including the Microsoft Cloud Background Check.
Master's Degree in Computer Science or related technical field and 12+ years of technical engineering experience (preferred).
Bachelor's Degree in Computer Science or related technical field and 15+ years of technical engineering experience (preferred).
Demonstrated ownership of a major platform, framework, runtime, or large-scale distributed system used in production by other engineering teams (preferred).
Experience with robot learning at scale, including vision-language-action policies, foundation models for robotics, imitation learning, reinforcement learning, or embodied artificial intelligence (preferred).
Experience deploying and operating robots in the real world at fleet scale, including fleet orchestration, over-the-air updates, and edge runtime (preferred).
Experience with robotics middleware (ROS, ROS2, Nav2, MoveIt, RViz, or Foxglove) and large-scale simulation tools like Isaac Sim, MuJoCo, Drake, or Gazebo (preferred).
Python
C++
Rust
Go
C#
Java
JavaScript
C
Kubernetes
Azure
ROS
ROS2
ONNX
TensorRT
Triton
CI/CD
API Gateway
Service Mesh
Edge Computing
Distributed Systems
Model Serving
C++
Python
ROS 2
Linux
Arm
Embedded Systems
Real-time Systems
IPC
Simulation
Hardware-in-the-Loop
Software-in-the-Loop
Heterogeneous Computing
SDKs
APIs
Python
C++
Robot Learning
Reinforcement Learning
Embodied AI
SLAM
Sensor Fusion
MPC
Trajectory Optimization
Foundation Models
Formal Methods
Mechatronics
Distributed Systems
Real-time Systems
CPU
GPU
NPU
MCU