Full-Stack ML Platform Engineer (RL Data Tools)

Clera; Oregon; Hybrid; USD 130,000 - 225,000; Full time

Benefits offered by this job

Visa sponsorship

Job summary

Clera is seeking an experienced software engineer to build product interfaces, backend systems, and tools for an AI reinforcement learning data platform. You will collaborate with research engineers and partners to translate complex requirements into intuitive products for creating, evaluating, and improving training data.

You will develop tools for browsing environments, review task quality, and understand model behavior, while enabling partner workflows for environments and data.

Qualifications

• 3+ years of full-stack production-grade software experience.
• Proficiency in Python and modern web stack (React/TS/Next.js).
• Experience with AI/ML/RL and end-to-end product ownership.
• Backend services, APIs, databases, and cloud infra (AWS) experience.
• Familiarity with dashboards/observability tools.
• Experience with data workflows, evaluation platforms valuable.
• Strong cross-team communication.

Responsibilities

• Develop tools for browsing environments, trajectories, task quality.
• Build partner workflows for environments and training data.
• Create dashboards and observability tools for quality, results, data collection.
• Design backend services and APIs connecting authoring, data collection, evaluation and training infra.
• Collaborate across research, operations, and go-to-market teams to ship useful systems.

Skills

Full-stack

Python

React/TypeScript

AI/ML/RL

Product ownership

Cloud infrastructure

Education

Bachelor's degree in CS

Tools

Docker

CI/CD

AWS

Kubernetes

Terraform

Grafana

Job description

Clera is seeking an experienced software engineer to build product interfaces, backend systems, and tools for an AI reinforcement learning data platform. You will collaborate with research engineers and partners to translate complex requirements into intuitive products for creating, evaluating, and improving training data.

You will develop tools for browsing environments, review task quality, and understand model behavior, while enabling partner workflows for environments and data.