Design and implement backend services, APIs, and workflows that support autonomy development — including learning, evaluation, simulation, and operational analysis.
Build and operate systems for orchestrating jobs and tasks across distributed environments, including containerized and clustered execution.
Design, implement, and maintain reinforcement learning training workflows: training loop orchestration, metrics collection, checkpointing, and experiment tracking.
Develop tooling and interfaces that visualize high-dimensional, time-varying autonomy data — telemetry, model outputs, learning artifacts, and simulation results.
Approach feature development from an AI-first perspective, designing tools around how autonomy engineers reason about data, model performance, and failure modes.

Requirements

7–10 years of professional software engineering experience
Strong proficiency in Go and Python, with production backend experience in both.
Prior exposure to C++.
Fluency in API design, service ownership, and data modeling.
Experience building or operating task and job orchestration systems for ML or data workloads.
Deep care for developer experience and user experience when building internal platforms and tools.
Ability to take initiative, move quickly, and operate effectively in fast-paced environments.
Taste matters more than syntax — you understand system architectures deeply and use frontier AI tooling to ship faster without losing that understanding.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

GoPythonC++API designdata modelingbackend servicesreinforcement learningjob orchestration systemsmetrics collectioncheckpointing

Soft Skills

initiativefast-paced environmentdeveloper experienceuser experiencetaste in system architecture