We are seeking an experienced Sr. Rust Engineer focused on Code Reasoning & Benchmarking. The role involves designing algorithmically rich coding problems, building evaluation systems, and developing comprehensive benchmarks that test reasoning, correctness, and performance.
This is a highly technical position requiring deep expertise in algorithms, system-level problem solving, and software engineering. The ideal candidate will be a creative problem designer and a detail-oriented engineer who can deliver production-ready artifacts within a short timeframe.
Key Responsibilities
• Problem & System Design: Create algorithmically challenging coding problems that evaluate reasoning, correctness, and efficiency in real-world software scenarios.
• Robust Development: Write clean, modular, and production-quality Java code along with comprehensive test suites covering correctness, edge cases, and performance.
• Technical Specifications: Draft clear, precise, and unambiguous specifications and problem statements with well-defined constraints and evaluation criteria.
• Algorithm Coverage: Ensure strong representation across multiple domains including data structures, graph algorithms, number theory, performance optimization, and constraint-based design.
• Metadata & Documentation: Apply structured metadata to all problems including taxonomy, difficulty levels, and domain relevance to maintain consistency and reproducibility.
• Quality Assurance: Participate in peer reviews and validation cycles to maintain high engineering and system integrity standards.
• Deliverables: Provide well-documented, maintainable, and scalable outputs ready for integration into production environments or downstream applications.
Requirements
• Experience: 5+ years in software engineering, algorithm design, or systems-level programming.
• Language Proficiency: Strong command of Rust (4+ years) with ability to implement high-performance solutions.
• Algorithmic Strength: Solid understanding of complexity analysis, optimization, and computational constraints.
• Test Engineering: Hands-on experience with test automation, benchmarks, or large-scale evaluation systems.
• Tooling Knowledge: Familiarity with version control (e.g., Git) and structured data formats (JSON, YAML).
Domain Expertise
Candidates should demonstrate 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, FFT, Linear Programming