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2 days ago
The Code Reasoning / Code Benchmarks role involves designing algorithmically rich coding problems and evaluation systems that test reasoning, correctness, and performance.
You will develop robust code, clear technical specifications, and comprehensive test suites across areas like data structures, graph algorithms, and number theory.
The role requires strong software engineering skills, a deep understanding of algorithmic complexity, and experience with benchmarking or test automation.
- Design algorithmically rich coding problems and systems that challenge reasoning, planning, and correctness in real-world software scenarios.
- Develop high-quality software solutions and comprehensive test suites, ensuring code robustness, correctness, and coverage across edge cases.
- Craft clear, unambiguous technical specifications and problem statements, balancing creativity and engineering precision.
- Ensure thorough coverage across algorithmic and systems domains, including classical data structures, performance engineering, mathematical logic, and constraint-based design.
- Apply structured metadata and documentation to development tasks, capturing taxonomy, difficulty, domain relevance, and reliability metrics.
- Participate in peer reviews and quality assurance processes to uphold rigorous engineering standards and system consistency.
- 5+ years of experience in software engineering, algorithm design, or systems-level programming.
- Strong proficiency in R with at least 4+ years of experience.
- Proven ability to write clear, concise, and technically challenging algorithmic code.
- Strong understanding of algorithmic complexity, performance optimization, and computational constraints.
- Experience with test automation, benchmark creation, or complex systems evaluation is a strong plus.
- Familiarity with modern software data formats (e.g., JSON, YAML) and version-controlled codebases.
Domains of Expertise: Successful candidates will demonstrate deep fluency in at least four of the following areas:
- Core Data Structures: Trie, Segment Tree, Union Find
- Algorithmic Paradigms: Dynamic Programming, Greedy Algorithms, Bitmasking
- Graph Algorithms: Shortest Paths, Network Flow, Topological Sorting
- Mathematics & Number Theory: Geometry, Probability, Modular Arithmetic
- String Processing: Suffix Trees, Rolling Hashing, Pattern Matching
- Advanced Topics: 2-SAT, Fast Fourier Transform (FFT), Linear Programming
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