仕事内容

About the Role

This position involves contributing to the assessment and enhancement of advanced AI coding models through detailed technical evaluations. The focus lies on practical machine learning engineering workflows and the rigorous evaluation of AI models. Availability is limited and candidates are selected on a first-come, first-served basis.

Role Responsibilities

Utilize cutting-edge AI coding agents to execute and assess sophisticated machine learning and AI engineering tasks.
Review model-generated code related to training, inference architectures, machine learning operations (MLOps), and large language model (LLM) implementations.
Detect bugs, handle edge cases, identify performance bottlenecks, and recognize failure modes.
Analyze outputs from various leading AI models to determine their comparative advantages and limitations.
Apply professional engineering insight to realistic machine learning engineering problems.

Work Commitment

The project operates on sprint cycles typically lasting between 12 to 24 hours, adjusted per client needs.

Candidate Requirements

Minimum of two years of professional experience in machine learning engineering.
Experience in developing production-level ML systems, deployment pipelines, LLM applications, or AI-driven product solutions.
Regular use and familiarity with AI coding assistants such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI or similar technologies.
Ability to critically assess model-generated ML implementations and make informed technical judgments.
Preferred experience in deploying machine learning models to production environments.

Compensation Details

Earn $400 for every approved task completed.
Typical tasks require roughly 2 to 3 hours post initial ramp-up time.
Payment is contingent upon task acceptance.

Additional Information

All qualified candidates will be considered regardless of legally protected characteristics. Reasonable accommodations are available upon request.

Machine Learning Engineer (Coding Agent Experience)

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