Sr. Python Engineer focused on Code Reasoning
2 weeks ago
We are seeking an experienced Sr. Python 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 python (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
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