Senior Engineer - Methods

Responsibilities & Key Deliverables

As a Senior Engineer within the NVH Simulation department at Mahindra & Mahindra Ltd, your primary responsibility will be to leverage engineering simulation and test data to develop insightful and predictive machine learning models. You will design, implement, and validate advanced AI algorithms that enhance product performance and efficiency.

Your role includes:

• Translating complex engineering and simulation data into actionable insights and robust predictive models that drive key business decisions.
• Developing scalable machine learning pipelines and incorporating deep learning methods, including geometrical deep learning, to address engineering challenges.
• Applying expertise in Python and related libraries such as Keras, TensorFlow, PyTorch, Torch_geometric, Open3D, NumPy, scikit-learn, and pandas to build and optimize models.
• Ensuring the rigor and reliability of models by conducting validation assessments, parameter hypertuning, and incorporating business context for continuous improvement.
• Integrating machine learning solutions into existing engineering processes to enhance end-to-end operational workflows efficiently and effectively.
• Managing data preparation including cleansing, transformation, and formatting, especially CAE (Computer-Aided Engineering) deck files and pre/post-processing for CAE software.
• Documenting technical specifications, methodologies, and functional use cases to facilitate knowledge sharing and support ongoing application development and maintenance.
• Collaborating cross-functionally with engineering teams, data scientists, and stakeholders to ensure alignment of machine learning solutions with organizational objectives.
• Staying updated on emerging machine learning technologies and engineering trends to maintain a competitive edge in product development.

Experience

The ideal candidate will be a graduate or postgraduate professional with 3 to 6 years of experience specifically focused on data-driven predictive model development, machine learning, and deep learning techniques within an engineering context.

Candidates should demonstrate a proven track record of applying advanced analytical methods and AI-based strategies to real-world engineering problems, preferably within simulation or automotive environments. Experience in building, tuning, and deploying end-to-end machine learning models is essential.

Strong familiarity with Python programming and associated machine learning frameworks such as TensorFlow, Keras, PyTorch, and data manipulation libraries like Pandas and NumPy is required.

An ability to interpret complex engineering datasets, including CAE files, and convert them into meaningful predictive insights is highly desirable.

Industry Preferred

Preference will be given to candidates with practical experience in the Automotive sector or Engineering Services industries. Familiarity with the specific challenges and applications related to Noise, Vibration, and Harshness (NVH) in automotive product development will be advantageous.

Experience working in multidisciplinary engineering teams and exposure to simulation-driven product design processes will further support success in this role.

Qualifications

Applicants should possess a Bachelor’s degree (B.E. / B.Tech) or a Master’s degree (M.E. / M.Tech) in Engineering or a closely related technical discipline. Degrees focusing on Mechanical Engineering, Computer Science, Data Science, or similar fields with strong emphasis on analytics and simulation are preferred.

Academic credentials should reflect strong foundational knowledge in mathematics, programming, and engineering principles to ensure capability in modeling complex systems.

General Requirements

General requirements include:

• Analytical Skills & Strong Math Background: Ability to analyze diverse datasets and understand statistical and mathematical models that underpin machine learning algorithms.
• Python & Machine Learning Proficiency: Deep understanding of programming best practices, development of machine learning workflows, and familiarity with key libraries and frameworks.
• Engineering Fundamentals: Solid grasp of fundamental engineering concepts, particularly those related to mechanical systems and NVH simulation.
• Systematic Problem Solving: Structured approach to identifying problems, devising potential solutions, and applying these while considering constraints and resources.
• Continuous Learning: Demonstrated motivation to explore novel technologies, stay abreast with latest industry standards, and apply innovative approaches to existing challenges.

Our commitment to Diversity, Equity, and Inclusion

At Mahindra and Mahindra Limited, our commitment to Diversity, Equity, and Inclusion (DEI) is foundational to fostering innovation and excellence across all facets of our organization.

We actively cultivate a respectful, supportive environment where all individuals are empowered to contribute authentically and reach their highest potential. Our recruitment and employment practices are intentionally inclusive, ensuring fair opportunities for candidates from all backgrounds, including those defined by age, caste, race, ethnicity, religion, gender identity, nationality, physical or mental abilities, sexual orientation, educational background, and other protected characteristics.

We welcome and encourage applications from diverse talent pools, recognizing that the broad spectrum of perspectives and experiences enriches our teams and drives continuous improvement.

Accessibility and inclusivity are integral to our hiring processes, and we commit to providing accommodations as needed to support all applicants.

Together, by embracing difference and fostering equity, we build a stronger future that reflects the vibrant communities we serve and the broad marketplace in which we operate.