We are seeking a highly skilled Cython Developer with expertise in performance optimization and low-level programming to join our dynamic team. The ideal candidate will have strong proficiency in Python and C, with experience in optimizing performance-critical applications and building high-performance data processing systems.
Key Responsibilities:
- Design, develop, and optimize performance-critical Python applications using Cython for significant speed improvements.
- Profile Python code to identify bottlenecks and refactor with Cython to enhance execution speed and memory efficiency.
- Write and compile Cython code, integrating C/C++ libraries with Python applications for optimal performance.
- Develop high-performance data structures and algorithms using SIMD and multi-core optimizations.
- Collaborate with data scientists and engineers to optimize scientific computing libraries like NumPy, SciPy, and pandas.
- Write and maintain unit tests and integration tests to ensure code quality and reliability
- Manage memory manually and implement low-level programming techniques for resource-intensive applications.[2]
- Create and maintain technical documentation for optimized codebases and performance benchmarks
- Work with cross-functional teams to understand performance requirements and deliver scalable solutions
- Participate in code reviews and contribute to best practices for performance engineering
Required Skills & Experience:
- 6–8 years of hands-on experience in Python development with focus on performance optimization.[3][4]
- Strong proficiency in Python and C/C++ programming languages.
- Deep expertise in Cython syntax, extensions, and performance optimization techniques.
- Experience with profiling tools and performance analysis to identify and resolve bottlenecks.
- Solid understanding of low-level programming concepts, including memory management and pointer operations.
- Familiarity with compiler tools such as gcc and clang for building optimized binaries.
- Strong experience with NumPy, SciPy, pandas, or other scientific computing libraries.
- Knowledge of data structures, algorithms, and system design principles.
- Experience with Git and version control practices
- Understanding of parallel programming, multi-threading, and asynchronous processing.
- Ability to work independently and manage multiple priorities in a fast-paced environment
Preferred Qualifications:
- Experience with JIT compilation techniques such as Numba or PyPy.
- Knowledge of SIMD instructions and vectorization for performance gains.
- Familiarity with data analytics frameworks and caching optimization.
- Experience working with high-stakes, large-scale production infrastructure.
- Knowledge of RESTful services and backend development using Python frameworks
- Bachelor's or master's degree in computer science, Software Engineering, or related field
