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Electric Vehicles Designs Internship
Electric Vehicles Designs Internship

Electric Vehicles Designs Internship at LetsIntern · Remote only · 0 - 1 years · ₹12000 - ₹18000 / mo · Profitable · Remote only · Posted 16 Sep 2026

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Electric Vehicles Designs Internship

Ashish Singh's profile picture
Posted by Ashish Singh
0 - 1 yrs
₹12000 - ₹18000 / mo
Remote only
Skills
Power Electronics
Electronics
Embedded C

Power Electric Vehicles with embedded software for battery management and autonomous driving.


What you'll do:

  • Develop BMS algorithms (SOC/SOH estimation)
  • Implement CAN bus communication protocols
  • Code motor control algorithms (FOC, sensorless)
  • Build ADAS features (ultrasonic parking, vision)
  • HIL testing with Vector tools
  • Optimize for automotive-grade reliability (AUTOSAR)

What we need:

  • C/C++, Embedded Linux/RTOS
  • Microcontroller experience (STM32, NXP)
  • Control systems or automotive interest
  • Debugging skills (oscilloscopes, logic analyzers)

Future-proof skills:

  • Work on actual EV prototypes
  • Portfolio for Tata, Mahindra EV teams
  • Automotive cybersecurity exposure
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About LetsIntern

Founded :
2021
Type :
Services
Size :
0-20
Stage :
Profitable

About

Apply for internship programs in 2026 at LetsIntern. Work on real industry projects, gain certificates, stipends & job-ready skills.

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Candid answers by the company

What is the location preference of jobs?

Bengalore,mumbai,Delhi,Chennai

Company social profiles

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About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.



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AI coding tools will be part of the workflow. We expect you to understand the underlying software well enough to build and debug without an LLM, then use AI to accelerate implementation, exploration and verification. You remain accountable for the result.


What you will own

• End-to-end delivery: clarify requirements, break work into achievable steps, implement features, test them, deploy them and respond to issues after release.

• Product decisions: understand the user problem, question unclear requirements and explain trade-offs between speed, quality, complexity and maintainability.

• Reliable software: investigate defects, identify root causes and improve error handling, performance and usability.

• Engineering continuity: maintain readable code, useful documentation and clear handovers so that others can run, understand and extend your work.


Engineering expectations

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Software fundamentals

• Programming: practical fluency in at least one programming language, with an understanding of data structures, control flow, modularity and common complexity trade-offs.

• Applications and services: understand how interfaces, APIs, business logic and data storage interact. Be able to trace a failure across these boundaries.

• Data: work with databases, reason about data models and queries, and handle validation, consistency and errors appropriately.

• Development workflow: use Git confidently, review changes, manage dependencies and keep development and deployment instructions reproducible.

• Testing and debugging: reproduce failures, form hypotheses, inspect logs and isolate causes. Test important behaviour and edge cases rather than relying on a successful demo.

• Security and reliability: recognise basic risks around authentication, access control, secrets, input handling and third-party dependencies.


Build independently. Use AI effectively.

• Without LLMs: write and modify code, diagnose defects, explain design choices and use documentation to solve unfamiliar problems independently.

• With AI coding tools: frame tasks clearly, supply relevant context, use generated suggestions selectively and inspect the resulting changes.

• Verify before accepting: check correctness, integration, security and maintainability. Recognise invented APIs, fragile assumptions and plausible-looking code that does not solve the actual problem.

• Protect information: use approved tools and handle credentials, proprietary code and user data responsibly.


Evidence we want to discuss

Be prepared to walk through a project you contributed to: the problem, your specific contribution, important technical decisions, a difficult bug and how you verified the result. Public repositories or demos are useful where available; do not share confidential material from previous employers.


Ownership, growth & applying

How you will work

• Act as an owner: follow through on agreed deliverables, raise blockers early and communicate progress with concrete evidence.

• Work with the team: collaborate with product and engineering colleagues, accept review constructively and explain technical choices clearly.

• Learn with purpose: pick up unfamiliar tools when the problem requires them, while keeping the solution proportionate to the need.

• Grow through contribution: begin with hands-on individual-contributor responsibility, with potential to take on broader product or team responsibility as delivery, judgement and collaboration develop.


What strong performance looks like

Working features that meet agreed requirements; clear reasoning about implementation; defects investigated systematically; code that others can maintain; and AI-assisted work whose quality you can explain and verify.


Eligibility and compensation

Experience: 1-5 years of hands-on software development experience only.

Freshers are not considered.

Locations: Bengaluru and Belagavi.

Annual CTC : 6-10 LPA

The offer will depend on experience, interview performance and growth potential.


What to expect in the assessment

Be prepared for a discussion of your previous work, a practical coding or debugging task without LLM assistance, and an assessment of how you use AI coding tools and verify their output. We will also discuss product judgement, ownership and collaboration.

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Shubham Vishwakarma

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