Full-Stack Software Engineer, Reinforcement Learning

San Franciscofull time

Remote

mid

$130k–$225k

H1B: yes

Clera Full-Stack Software Engineer, Reinforcement Learning at Clera builds product interfaces, backend systems, and internal tools for a reinforcement learning data platform. The role involves developing tools for data inspection, partner workflows, dashboards, and backend services to support research and operations teams.

Responsibilities

Build product interfaces, backend systems, and internal tools for a reinforcement learning data platform. You will own experiences that help research teams and external partners create, evaluate, and improve training data, working closely with research, operations, and go-to-market teams.
Develop tools for browsing environments, inspecting trajectories, reviewing task quality, and understanding model behavior.
Build partner workflows for creating, submitting, testing, and iterating on reinforcement learning environments and training data.
Create dashboards and observability tools for environment quality, evaluation results, data collection progress, and pipeline health.
Design backend services and APIs that connect task authoring, data collection, evaluation, quality assurance, and training infrastructure.
Work with cross-functional teams to turn ambiguous needs into polished products and ship improvements quickly.

Qualification

Hands-on experience with AIExperience building backend servicesComfort with cloud infrastructureExperience with data inspectionStrong product judgmentExperience with AWS

Required

At least 3 years of full-stack engineering experience building and shipping production systems, with technical field study or equivalent technical fundamentals.
Proficiency in Python and a modern web stack such as React, TypeScript, or Next.js.
Hands-on experience with AI, machine learning, or reinforcement learning, and experience owning products from design through deployment.
Experience building backend services, APIs, and databases, as well as dashboards, monitoring tools, or observability interfaces.
Comfort with cloud infrastructure, Docker, CI/CD, and production debugging.
Experience with data inspection, review, quality assessment, data collection, labeling, or evaluation tools is valuable. AWS, Kubernetes, Terraform, and Grafana experience is also useful.
Strong product judgment, independent execution, and communication across technical and non-technical teams.

Preferred

Experience with data inspection, review, quality assessment, data collection, labeling, or evaluation tools
Experience with AWS, Kubernetes, Terraform, and Grafana

Company

Clera

View company page

Source: ashby

Active within the past hour

Remote-friendly

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