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Software Developer - Automotive Switch & Ethernet Expert

BMW Techworks India

  • Pune, India
  • Competitive Package (Best in Industry)
  • 3-8 Yrs
  • Posted Today
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About the role

Role & responsibilities Be part of the ECU Platform Development team, responsible for Ethernet connectivity and Ethernet switch integration for next-generation central ECUs. Design, develop, configure, and integrate Automotive Ethernet communication and switch-management solutions. Work closely with software architects, low-level software developers, hardware specialists, and system engineers.

Contribute to the integration and optimization of Ethernet networking across the ECU platform. Analyze and resolve complex Ethernet and networking-related issues, including software-hardware integration problems. Collaborate in an international and interdisciplinary environment with internal teams and high-tech industry partners.

Independently coordinate technical activities and drive topics with relevant stakeholders. Preferred candidate profile University degree in Computer Science, Electrical/Electronics Engineering, or a comparable field, or equivalent professional qualification. Strong proficiency in C++ and solid knowledge of software development best practices.

Strong knowledge of IEEE 802.3 Ethernet networking, including OSI Layers 13 and their associated software stacks. Hands-on experience with networking concepts and protocols such as VLAN, TCP/IP, UDP, and QoS. Experience in Automotive Ethernet switch configuration, integration, and management.

Good understanding of Ethernet switching, routing, network interfaces, and traffic management. Familiarity with network security technologies such as IPsec and MACsec. Experience with embedded RTOS-based systems, preferably in an automotive environment.

Familiarity with automotive communication technologies such as CAN, LIN, and FlexRay. Strong analytical and troubleshooting skills with the ability to debug complex networking issues. Knowledge of Python or other scripting languages is advantageous.

A proactive mindset with creative ideas and openness to innovative software technologies for the mobility of the future.[

Eligibility & process

Who can apply

Experience: 3-8 Yrs. Open to matching qualifications.

Skills & stack

Network Configuration RTOS Automotive Automotive Infotainment OSI Ethernet TCP Python

Selection process

  1. Online Assessment / Technical Interview Rounds / HR Review

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Network Configuration, RTOS, Automotive, Automotive Infotainment, OSI, Ethernet, TCP, Python) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion BMW Techworks India Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join BMW Techworks India as a Software Developer - Automotive Switch & Ethernet Expert?
Highlight BMW Techworks India's market reputation, recent tech innovations, and how your skills in Network Configuration directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
BMW Techworks India Competitive Package (Best in Industry)
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