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Compensation: USD 50 – 125/hour
Hours: 10 to 40 hours/week (Partial PST overlap required)
Experience Required: 10 – 25 Years
Contract Duration: 1 Month (Extension based on performance)
Notice Period: Immediate preferred
Note
- This is a contract-based, fully remote opportunity.
- Contractors must be citizens or valid work permit holders in the US, Canada, Australia, or approved Western European countries.
- No medical benefits or paid leave.
- The contractor is responsible for managing their own taxes and compliance.
- Payments are made based on actual hours worked.
- We're looking for highly experienced Fullstack Engineers to work on frontier AI projects, especially around improving Large Language Models (LLMs) for software engineering tasks. You'll support the development of LLM training and evaluation datasets by assessing code generated by models, building agent-based tools, and analyzing complex real-world software.
- You’ll work with teams pushing the boundary of AI-assisted development to identify weaknesses in model behavior and provide detailed code assessments. The goal is to build smarter, more context-aware AI coding tools that function in realistic development environments.
- Work across multiple LLM-related projects aimed at improving AI model performance on code.
- Lead end-to-end engineering efforts for agent use cases like home automation, coding copilots, and creative assistants.
- Review and rank model-generated code snippets using a structured evaluation system.
- Evaluate code diffs for correctness, style, maintainability, and performance.
- Build scalable fullstack applications to support dataset pipelines and tooling.
- Collaborate with researchers to uncover edge cases and complex code behaviors.
- Write clear, structured rationales to explain code assessment outcomes.
- 10+ years of experience in software engineering with strong fullstack capabilities.
- At least 2–3 years as a full-time employee (not contractor) at a top-tier tech company (e.g., Google, Meta, Microsoft, Amazon, Stripe, etc.).
- Deep expertise in software architecture, debugging, and code review.
- Proven ability to assess large, realistic codebases and evaluate code quality.
- Strong written and oral communication for clear and logical evaluations.
- Hands-on experience with Git, code versioning, modern frameworks, and cloud platforms.
Key Skills
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