Job Description:
We are developing an edge-AI system for real-time detection, mapping, and alerts. The role involves building computer vision models, embedded firmware,
and on-device intelligence that can accurately detect anomalies under diverse real-world conditions.
Key Responsibilities
- Develop, train, and fine-tune computer vision models (YOLO family, detection/segmentation frameworks)
- Create and manage datasets, including data collection, cleaning, and annotation
- Optimise ML models for embedded devices (quantisation, pruning, TensorRT/TFLite/ONNX acceleration)
- Integrate and calibrate cameras, IMUs, GNSS, and other sensors for road-condition monitoring
- Build firmware and on-device processing pipelines using Python/C++ on platforms like Jetson, Raspberry Pi, and ARM MCUs
- Conduct field tests on various environments, benchmark accuracy, and iterate model improvements
- Work with hardware and software teams to convert prototypes into reliable, production-ready systems
What We Offer
- Internship:
- Stipend: ₹5,000/month + upto ₹5,000 performance bonus
- PPO opportunities for exceptional candidates with a CTC range of ₹3–6 LPA
- Full-time:
- CTC: ₹3–6 LPA (Based on expertise and role fit)
- Certificate & Letter of Recommendation
- Flat, ownership-driven culture with direct mentorship from founders and professors
- Collaborative, engineering-driven environment focused on R&D and rapid iteration
What You"ll Gain
- Hands-on experience with cutting-edge edge-AI, computer vision, and embedded systems
- Real-world exposure to deploying AI models in dynamic outdoor environments
- Experience in system optimisation, sensor fusion, and hardware-software co-design
- End-to-end understanding of taking a deep-tech product from prototype to pilot to scale
- Opportunity to lead modules and shape the core technology in a fast-growing startup
Desired Candidate Profile
- Strong fundamentals in deep learning and computer vision (CNNs, detection architectures)
- Hands-on experience with YOLO (v5/v8/v9), PyTorch/TensorFlow, and OpenCV
- Experience training custom datasets for detection tasks
- Proficiency in Python and working knowledge of C/C++ for embedded programming
- Experience with Jetson, Raspberry Pi, or ARM-based embedded platforms
- Familiarity with camera integration, sensors (IMU/GPS), and IoT protocols
- Good debugging skills, problem-solving ability, and willingness for field testing
Hiring Process
- Application Screening: Resume + portfolio
- Design Assignment: A task to access your technical and creative ability
- Interview (Google Meet or In-person): Discussion on assignment, problem-solving approach, and fit with the team
How to Apply
- Please share your resume with your portfolio to core.atsc@gmail.com