drivebuddyAI
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Ahmedabad · Hybrid · 8-11 Yrs · Aug 18
Computer Hardware Development · 1 to 50 Employees · New Delhi, India
drivebuddyAI founded in 2018 with an aim to introduce driving safety as a aftermarket component to commercial vehicles to enhance driving safety & improve driving behavior to make the ecosystem more safer and more data driven. We believe that the road to autonomy starts from ADAS & Telematics. We have a vision to Build an AI Nervous System, that comprehends human behavior to augment the decision-making capabilities, thereby empowering the Future Mobility Ecosystem. drivebuddyAI aims to accelerate the evolution in the future of mobility through the transformation of the Fleet Management & Insurance Ecosystem.
Hiring: Engineering
What employees say
+ You will learn a lot and how to deal with Micro Management and live without salary.
− Extreme Micro Management, Salaries are always delayed by 1-3 months—but deadlines and tasks they want on time to be completed. Also, expect to work on every Weekend.
More reviews on the company profile.
Interview experience · Backend Developer
It was scheduled for an hour. The interviewer was cooperative. It started with some coding questions. Then one database question. The interviewer was giving clues when stuck and was asking if the question was clear. Init
Average difficulty · Gurgaon, Haryana · 1 reports
More interview insightsJob description
Overview
Function: Engineering → AI / Deep Learning
Responsibilities
- Design and develop state-of-the-art deep learning models for perception tasks such as object
- detection, lane detection, semantic segmentation, tracking, and driver monitoring.
- Work on multi-sensor fusion (camera, LiDAR, radar, IMU) for autonomous systems
- Lead model training, evaluation, validation, and optimization pipelines
- Optimize AI models for edge deployment (latency, memory, and compute constraints)
- Deploy models on embedded platforms with hardware accelerators (GPU, NPU, VPU)
- Collaborate with embedded, hardware, and systems teams for real-world integration
- Drive robustness improvements across varying weather, lighting, and road scenarios
- Ensure compliance with automotive safety and validation standards
- Review architecture decisions and mentor junior AI engineers
- Contribute to research-driven innovation while maintaining production focus
- 8–12 years of experience in Deep Learning / Computer Vision
- Proven industry experience working on Autonomous Vehicle or ADAS systems
- Strong proficiency in Python and C++
- Deep expertise in PyTorch and/or TensorFlow
- Hands-on experience with perception models (Detection, Segmentation, Tracking)
Qualifications
- Architecting and deploying deep learning models for autonomous driving
- Leading perception and vision-based AI development
- Building production-grade AI systems for real-world automotive environments
- Mentoring AI engineers and driving technical excellence
- Strong understanding of model optimization for edge deployment (ONNX, TensorRT,
- quantization)
- Strong mathematical foundation (linear algebra, optimization, probability)
- Proven track record of deploying production-grade AI systems
- Exposure to ISO 26262 or automotive safety standards
- Research publications or patents in autonomous systems
- Work on cutting-edge AI technology with real-world impact
- Collaborate with a talented, mission-driven team
- Solve complex challenges in computer vision, embedded systems, and automotive safety
- Grow with a company poised for global expansion in a high-growth industry
- Continuous Learning: We believe the best AI, like the best people, never stops improving.
- Real-World Impact: We measure success by lives saved and roads made safer.
- Technical Excellence: We build robust, validated, production-ready systems.
- Collaborative Innovation: Great ideas come from diverse minds working together.
- Competitive Salary & Benefits
- OKR-driven appraisals
- Flexible Leave Policy
- Employee Skill Enhancement
- Highly dynamic work culture
- Opportunity for equity participation
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