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1–2 jobs· newest first

Full-Stack Software Engineer, DesignNew
Clera · San Francisco, US+2 more
$130K–$225KVisa
Founding EngineerNew
Raydar · San Francisco, US
$150K–$300KOn-site · Full-time

+10K new in the last hour

Full-Stack Software Engineer, Design

Clera · Posted Nov 13, 2026

San Francisco, California, United States +2 more
$130K–$225K per year
3+ years
Visa sponsorship

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AI

Apply on careers page

Design and build interfaces across the platform and marketplace, taking ideas from early concepts through launch.

Locations (3)

San Francisco, California, United States
United States
Singapore

Compensation

Base salary range: $130,000 to $225,000 USD annually. Visa sponsorship is available.

Responsibilities

Design and build interfaces across the platform and marketplace, taking ideas from early concepts through launch.
Make agent runs, evaluation results, reward signals, and quality feedback understandable and actionable.
Partner with research and engineering teams to turn complex reinforcement learning and evaluation workflows into useful tools.
Talk with users, observe where they struggle, and improve the product based on feedback.
Create thoughtful interaction patterns and maintain high standards for usability, visual quality, and implementation.

Requirements

Technical education

Skills

Front-end skills Design-engineering work Visual design User feedback Developer tools Data-rich products Research software AI agents Evaluations Reinforcement learning Training data

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Founding Engineer

Raydar · Posted Nov 10, 2026

San Francisco, California, United States
On-site
Full-time
$150K–$300K per year
1–7 years

Apply with RefersoAI Apply on careers page

Design and build test environments, evaluation harnesses and labeled datasets that measure how AI systems behave across multi-step tasks.

Compensation

Base salary: USD 150,000 to 300,000

Responsibilities

Construct simulated software environments that mimic the tools and workflows automated systems use.
Build grading logic and evaluation systems that hold up when systems look for shortcuts.
Create benchmarks whose scores track real-world results.
Review interaction logs to find and measure previously unrecorded failure patterns.
Turn findings into reusable datasets and test suites for internal improvement and external partners.

Requirements

Nice to have: found a real flaw in a widely used benchmark
Nice to have: caught a model gaming a grader and fixed the grader
Nice to have: built environments or benchmarks a leading AI lab used for training or evaluation
Nice to have: startup founding experience or participation in a selective fellowship
Nice to have: high-level competitive achievement in mathematics, programming, debate or games

Skills

training data post-training

evaluation for machine learning models

building or contributing to benchmarks

environments used to train or test models

replicating common business software

evaluation pitfalls

systems game metrics

Benefits

Equity
Health, dental and vision coverage
Retirement plan
Flexible time off

See full job description