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Senior Software Engineer – Python (LLM Evaluation & Repository Validation)

Company: Turing · Location: Remote — Worldwide · Type: contractor · Posted: 2026-09-19

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Elite AI Engineering Engagement

Shape the cognitive capabilities of next-generation artificial intelligence models by engineering verifiable software evaluation datasets with Turing.

The evolution of artificial intelligence has reached a critical juncture. Large Language Models (LLMs) can generate fluent text, but ensuring they can execute complex, real-world software engineering tasks remains one of the industry's greatest frontiers. Grounded software validation requires rigorous human expertise to build reliable benchmarks that test how AI interacts with actual source code, manages dependencies, and solves authentic coding bugs.

Turing—one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems—is engaging senior Python software engineers for a high-impact role: Senior Software Engineer – Python (LLM Evaluation & Repository Validation). This remote contractor opportunity invites you to combine elite software engineering with cutting-edge AI research.

Role Type
Contractor Assignment
Duration
3 Months (Start Next Week)
Commitment Options
20, 30, or 40 hrs/week

About the Project and Role

In this project, engineers build verifiable software engineering (SWE) tasks based on public repository histories using a synthetic approach with human-in-the-loop oversight. The objective is to expand dataset coverage across diverse programming languages, difficulty tiers, and architectural domains.

As a tech-lead-level contributor, your role involves hands-on software engineering work including development environment automation, issue triaging, and evaluating test coverage and quality. You will define how frontier AI models reason through complex codebases.

What Your Day-to-Day Looks Like

Your daily responsibilities blend deep technical engineering with analytical evaluation:

  • Issue Triaging: Analyze and triage GitHub issues across trending open-source libraries.
  • Environment Automation: Set up and configure code repositories, including Dockerization and local environment setup.
  • Quality Assurance: Evaluate unit test coverage and code execution quality.
  • Local Testing: Modify and run codebases locally to assess LLM performance in bug-fixing scenarios.
  • Research Collaboration: Work alongside AI researchers to design and identify repositories and issues that present genuine challenges for LLMs.
  • Leadership: Opportunities to lead a team of junior engineers collaborating on shared project milestones.

Are You a Fit? Required Skills & Experience

To succeed in this rigorous engagement, candidates should meet the following technical benchmarks:

  • Experience: Minimum 3+ years of overall professional software engineering experience.
  • Language Proficiency: Strong, demonstrated experience with **Python**.
  • Tooling Mastery: Proficiency with Git, Docker, and basic software pipeline setup.
  • Codebase Navigation: Exceptional ability to understand, navigate, and debug complex codebases.
  • Local Execution: Comfortable running, modifying, and testing real-world projects locally.
  • Open Source: Previous experience contributing to or evaluating open-source projects is a strong plus.
  • Nice-to-Haves: Participation in LLM research/evaluation or experience building developer tools and automation agents.

Engagement Details & Location Eligibility

This is a 3-month remote contract assignment with an expected start date next week. Candidates can choose among three time-commitment tiers: 20 hours/week, 30 hours/week, or 40 hours/week (minimum 4 hours per day, with at least a 4-hour daily overlap with PST).

Eligible Regions: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, and Mexico.

The Evaluation Process

To ensure high standards of technical excellence, the evaluation process is streamlined yet thorough (approximately 75 minutes total):

  1. Technical Round (60 minutes): In-depth technical assessment covering Python, system design, and debugging.
  2. Technical & Cultural Discussion (30 minutes): Collaboration, communication, and cultural alignment review.

Maximizing Your Success: Onboarding & Stability

Once selected, completing your onboarding promptly and diving into your first 10 hours of work is essential. Fulfilling this initial milestone guarantees project stability, solidifies your standing within the network, and unlocks access to more advanced tasks and ongoing assignments.


Ready to Shape the Future of AI?

Join Turing's elite network of software engineers and evaluate next-generation AI systems.
Submit your application through the secure official portal below.

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Responsibilities

  • Issue Triaging: Analyze and triage GitHub issues across trending open-source libraries.
  • Environment Automation: Set up and configure code repositories, including Dockerization and local environment setup.
  • Quality Assurance: Evaluate unit test coverage and code execution quality.
  • Local Testing: Modify and run codebases locally to assess LLM performance in bug-fixing scenarios.
  • Research Collaboration: Work alongside AI researchers to design and identify repositories and issues that present genuine challenges for LLMs.
  • Leadership: Opportunities to lead a team of junior engineers collaborating on shared project milestones.

Skills

  • Experience: Minimum 3+ years of overall professional software engineering experience.
  • Language Proficiency: Strong, demonstrated experience with **Python**.
  • Tooling Mastery: Proficiency with Git, Docker, and basic software pipeline setup.
  • Codebase Navigation: Exceptional ability to understand, navigate, and debug complex codebases.
  • Local Execution: Comfortable running, modifying, and testing real-world projects locally.
  • Open Source: Previous experience contributing to or evaluating open-source projects is a strong plus.

Apply now →