Full-Stack Software Engineer, Reinforcement Learning
At a glance
Mid-level Machine Learning Engineering role at Clera. San Francisco · full-time · $130,000–$225,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build tools to browse environments, inspect trajectories, assess task quality, and interpret model behavior
- Set up partner workflows for developing, submitting, testing, and improving environments and training data
- Create dashboards showing environment quality, evaluation results, collection progress, and pipeline health
- Develop services and APIs that link authoring, collection, evaluation, review, and training systems
- Coordinate with research, operations, and go-to-market teams to ship and improve software
What you bring
- At least three years developing production full-stack software, along with a technical education or background
- You can build with Python and a current web framework or language such as React, TypeScript, or Next.js
- You have practical AI, machine learning, or reinforcement learning experience and have taken products from design to deployment
- You have built backend services, APIs, and databases, and worked with cloud infrastructure, Docker, CI/CD, and production debugging
Who this fits
This mid-level role suits an engineer comfortable building both user-facing tools and backend systems, with hands-on AI or reinforcement learning experience. The position is on-site in San Francisco, with remote candidates considered if they can overlap substantially with San Francisco or Singapore working hours. Visa sponsorship is available for eligible full-time candidates.
From the employer
About the Role
Build the product interfaces, backend systems, and internal tools that support an AI reinforcement learning data platform. You will work with research engineers and external partners to turn complex requirements into intuitive products for creating, evaluating, and improving training data.
What You'll Do
Develop tools for browsing environments, inspecting trajectories, reviewing task quality, and understanding model behavior.
Build partner workflows for creating, submitting, testing, and iterating on 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 review, and training infrastructure.
Work across research, operations, and go-to-market teams to ship and improve useful systems.
What We're Looking For
At least 3 years of full-stack software engineering experience building and shipping production systems, with a technical education or background.
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 a track record of owning products from design through deployment.
Experience building backend services, APIs, and databases, as well as using cloud infrastructure, Docker, CI/CD, and production debugging practices.
Experience with dashboards, monitoring or observability tools, data inspection, review workflows, or quality assessment interfaces.
Experience with data collection, annotation, or evaluation platforms, and tools such as AWS, Kubernetes, Terraform, or Grafana, is valuable.
Strong product judgment, initiative, and communication across technical and non-technical teams.
Compensation & Benefits
Base salary is $130,000 to $225,000 USD annually. Visa sponsorship is available for eligible full-time candidates.
Location
On-site in San Francisco, California. Remote candidates may be considered if they can maintain 70% to 80% time zone overlap with San Francisco or Singapore.
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Machine Learning Engineering$130k+
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