Staff Systems Engineer

Gather AI • Pittsburgh, PA

2d

About The Position

We are looking for two Staff Systems Engineers to take technical ownership of one of our product platforms — Drone or MHE Vision — and bring systems-level rigor to how we build, deploy, and operate it at scale. Reporting to the Director of Autonomy, Brad Hammner, you will own the full vertical from hardware integration through cloud delivery, improving reliability, integration test coverage, deployment velocity, and cross-subsystem observability.
As a Staff Systems Engineer, you'll drive technical direction across teams, own outcomes end-to-end, and operate with direct visibility to product and company leadership.

Requirements

• 10+ years of engineering experience shipping production systems, with significant breadth across embedded/edge compute, cloud infrastructure, and data pipelines
• Systems architecture experience — must have designed and owned multi-subsystem platforms spanning hardware, edge compute, cloud, and data layers
• Cross-team technical leadership — demonstrated ability to drive alignment and delivery across 2+ engineering teams without direct authority
• Production deployment at scale — must have shipped and operated real systems with real reliability requirements, not just prototypes
• Python proficiency, Linux fluency, CI/CD tooling, Docker, and C++ familiarity; experience with embedded/edge platforms (Jetson, ARM)

Nice To Haves

• Robotics or drone systems experience (ROS, flight controllers, sensor integration, autonomy stacks)
• Computer vision or ML pipeline integration (model serving, inference optimization, data labeling pipelines)
• Cloud infrastructure and backend systems (AWS/GCP, infrastructure-as-code, scalable data pipelines)
• Warehouse or logistics domain experience (operational constraints, customer deployment patterns)

Responsibilities

• Take full technical ownership of an assigned product platform (Drone or MHE Vision) — understanding the system end-to-end and driving its reliability, scalability, and operational maturity
• Streamline the deployment pipeline to reduce friction and improve repeatability, including CI/CD for embedded and containerized components and fleet-wide update mechanisms
• Lead cross-subsystem integration hardening: edge-to-cloud data flow, model deployment pipelines, sensor-to-perception orchestration, and production monitoring and observability
• Establish and track product performance metrics (scanning accuracy, uptime, deployment velocity) and drive improvements across engineering teams
• Collaborate with Product Management on roadmapping, requirements translation, and customer deployment planning; conduct site visits to understand the product in its operating environment
• Drive technical alignment across the autonomy, ML, and cloud engineering teams

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed