C++ Software Engineer - Ai Training

Talantir; Germany; Remote; EUR 83,000 - 165,000; Full time

Job summary

Talantir seeks a skilled contractor to evaluate and improve AI systems focused on code reasoning, programming solutions, and technical explanations. You will rigorously assess LLMs in coding contexts and annotate results for accuracy, readability, and correctness.

You bring a CS degree, strong software engineering background, and proven ability to tackle medium-to-hard problems, with experience in open-source and LLM-based coding workflows. Remote work options are available.

Qualifications

• BS/MS/PhD in Computer Science or related field.
• Significant real-world software engineering experience.
• Expert in at least one programming language (Python/Java/C++/JS/Go/Rust).
• Ability to solve medium/hard coding problems independently.
• Contributions to well-known open-source projects with merged PRs.
• Experience using LLMs while coding and understanding limitations.

Responsibilities

• Evaluate LLM-generated coding and software eng outputs for accuracy and clarity.
• Fact-check using trusted sources and references.
• Execute code and validate outputs with appropriate tools.
• Annotate model responses noting strengths, weaknesses, and errors.
• Assess code quality, readability, algorithms, and explanations.
• Ensure responses align with conversational guidelines and policies.
• Follow established evaluation taxonomies, benchmarks, and guidelines.

Skills

Software engineering

Programming languages

LeetCode/HackerRank

Open source

LLMs coding

Attention to detail

Education

BS/MS/PhD in Computer Science

Job description

Work Mode: Remote

Engagement Type: Independent Contractor

Schedule: Full-Time or Part-Time Contract

Language Requirement: Fluent English

Role Overview

We partner with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems.

This project focuses specifically on evaluating and improving how AI systems reason about code, generate programming solutions, and explain technical concepts across various complexity levels.

The role involves rigorous technical evaluation of AI-generated responses in coding and software engineering contexts.

What You’ll Do

• Evaluate LLM-generated responses to coding and software engineering queries for accuracy, reasoning, clarity, and completeness
• Conduct fact-checking using trusted public sources and authoritative references
• Conduct accuracy testing by executing code and validating outputs using appropriate tools
• Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
• Assess code quality, readability, algorithmic soundness, and explanation quality
• Ensure model responses align with expected conversational behavior and system guidelines
• Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines

Who You Are

• You hold a BS, MS, or PhD in Computer Science or a closely related field
• You have significant real-world experience in software engineering or related technical roles
• You are an expert in at least one relevant programming language (e.g., Python, Java, C++, JavaScript, Go, Rust)
• You are able to solve HackerRank or LeetCode Medium and Hard–level problems independently
• You have experience contributing to well-known open-source projects, including merged pull requests
• You have significant experience using LLMs while coding and understand their strengths and failure modes
• You have strong attention to detail and are comfortable evaluating complex technical reasoning, identifying subtle bugs or logical flaws

Nice-to-Have Specialties

• Prior experience with RLHF, model evaluation, or data annotation work
• Track record in competitive programming
• Experience reviewing code in production environments
• Familiarity with multiple programming paradigms or ecosystems
• Experience explaining complex technical concepts to non-expert audiences

What Success Looks Like

You identify incorrect logic, inefficiencies, edge cases, or misleading explanations in model-generated code, technical concepts, and system design discussions

Your feedback improves the correctness, robustness, and clarity of AI coding outputs

You deliver reproducible evaluation artifacts that strengthen model performance