Cython Engineer

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.