MBSE Matlab/mScripting Requirement

Job Title:

• MBSE Matlab/mScripting Requirement
• Experience:
• • 4 - 5 Years
• Qualification:
• • B.E/B.Tech or M.E/M.Tech (ECE, Mechatronics)
• Job Location:
• • Chennai
• Job Description:
• • Thoroughly analyze existing MATLAB codebase, algorithms, data structures, and functionalities to gain a comprehensive understanding of their purpose, implementation details, and underlying mathematical/scientific principles.
  • Document the intricacies of the MATLAB tools, identifying core logic, dependencies, and potential challenges for migration.
  • Collaborate with end-users and domain experts of the current MATLAB tools to capture implicit requirements, usage patterns, and critical performance characteristics.
  • Develop detailed migration plans, including phased approaches, risk assessments, and resource estimates for converting MATLAB components to Python.
  • Design the architecture and data flow for the new Python-based tools, ensuring scalability, maintainability, and alignment with overall software engineering standards.
  • Select appropriate Python libraries, frameworks, and methodologies for optimal translation of MATLAB functionalities (e.g., NumPy for matrix operations, SciPy for scientific functions, Pandas for data handling).
  • Translate complex MATLAB algorithms and numerical methods into efficient, well-structured, and idiomatic Python code.
  • Implement new features or enhancements as identified during the migration process, leveraging Python's ecosystem.
  • Develop robust data processing pipelines and interfaces to integrate with existing or new data sources.
  • Design and implement comprehensive test suites (unit, integration, regression tests) to ensure functional correctness and numerical fidelity of the Python tools against their MATLAB counterparts.
  • Perform rigorous validation of results, comparing outputs from MATLAB and Python implementations to ensure accuracy and consistency.
  • Identify and resolve performance bottlenecks in the Python code, optimizing algorithms and data structures for efficiency.
  • Utilize profiling tools to benchmark and improve the execution speed of critical components.
  • Create clear, concise, and comprehensive technical documentation for the new Python tools, including design specifications, API documentation, user guides, and migration reports.
  • Provide training and mentorship to other team members on the new Python codebase and best practices for scientific computing in Python.
  • Contribute to establishing coding standards and best practices for scientific Python development within the team.
  • Work closely with cross-functional teams (e.g., software engineers, data scientists, domain experts) to ensure seamless integration of the migrated tools into existing systems and workflows.
  • Participate in code reviews, architectural discussions, and agile development ceremonies.
  • Manage version control (Git) for the Python codebase, ensuring proper branching, merging, and release management.
• Skill set:
• • MATLAB scripting, Python
• Domain Knowledge:
• • Expert-level knowledge of Python syntax, object-oriented programming, and common design patterns.
  • Deep understanding and hands-on experience with core scientific Python libraries:
  • NumPy, SciPy, Pandas,
  • Matplotlib, Seaborn, Plotly/Bokeh: For data visualization and graphical output replication.
  • Familiarity with other relevant libraries
  • Ability to read, understand, and debug complex MATLAB code, including knowledge of MATLAB's specific data types, functions, and programming paradigms.
  • Experience with MATLAB's toolboxes relevant to the existing tools
  • Understanding of MATLAB's plotting capabilities and GUI development
  • Solid understanding of common numerical algorithms, linear algebra, differential equations, optimization techniques, and statistical methods.
  • Ability to identify and address potential numerical precision issues during migration.
  • Proficiency with Git for version control.
  • Experience with unit testing (e.g., pytest) and integration testing frameworks.
  • Knowledge of code quality tools (linters like Flake8, Black) and static analysis.
  • Understanding of software design principles (SOLID, DRY).
  • Experience with various data formats (e.g., HDF5, CSV, Parquet, JSON, XML).