MBSE Matlab/mScripting Requirement - ZR_1961_JOB

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).