Senior/Lead Python Software Engineer Offline
Job Description
Required Qualifications:
β Masterβs or Ph.D. in Computer Science, Software Engineering, Applied Mathematics, or a related field.
β 10+ years of experience in Python development and software architecture, with a focus on designing, structuring, and managing complex computational systems.
β Strong background in numerical computing, statistical modeling, and algorithm optimization.
β Proven ability to translate complex mathematical models into efficient, maintainable, and scalable code.
β Expertise in implementing high-performance Python-based systems for complex computational tasks.
β Advanced understanding of data structures, algorithms, and software engineering best practices.
β Solid experience in optimizing code for performance and scalability.
β Strong ability to collaborate with cross-functional teams, particularly with statistical computing and reinforcement learning experts, to integrate and refine statistical machine learning algorithms.
β Demonstrated ability to maintain system robustness, reliability, and integrity in complex environments.
Preferred Qualifications:
β Experience working with high-performance computing environments.
β Familiarity with containerization and orchestration technologies (e.g., Docker).
β Knowledge of cloud platforms, and experience with AWS, Azure or Google Cloud) for deploying and managing computational systems.
β Experience with version control systems (e.g.,including Git)
β Knowledge of MLOps principles to enhance the development and deployment lifecycle of computational systems.
Job Responsibilities
β Design, implement, and optimize the DCL systemstatistical computing and reinforcement learning systems with a focus on high-quality, modular, and reusable Python code.
β Collaborate closely with mathematical experts to integrate complex statistical models and algorithms into the system.
β Ensure the robustness, integrity, and scalability of the system through careful architectural planning and performance optimization.
β Write clean, maintainable, and well-documented code that adheres to best practices in software engineering.
β Troubleshoot, debug, and optimize existing systems, focusing on performance and stability.
β Maintain and improve system performance while ensuring it meets the computational requirements of various tasks.
β Lead the architectural design of complex software systems.
Department/Project Description
Join a cutting-edge initiative to develop a next-generation, closed-loop causal knowledge generating reinforcement learning system based on proprietary and patented algorithmic methods. These advanced causal inference and reinforcement learning algorithms have already been deployed across multiple domains in a Fortune 500 company, powering applications ranging from e-commerce content generation and targeting to large-scale factory optimization and control.
This project will push the frontiers of adaptive learning and real-time decision-making, creating a modular, reusable codebase that can be flexibly redeployed across various high-impact systems. As part of this effort, the team will develop synthetic data generation systems to rigorously test and optimize these algorithms, ensuring they perform as if interacting with real-world environments.
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