At Mobilestack (Mobai Enterprise Pvt Ltd), we are pioneering the future of
smart systems powered by edge computing and artificial intelligence. We create
innovative solutions that push the boundaries of what is possible by deploying
AI models directly at the edge. Our mission is to redefine how data is
captured, analyzed, and acted upon in real-time, all while maintaining a focus
on efficiency and low latency.
**Please cosider applying to this position ONLY IF you have Video AI
processing experience** \- preferably with GITHUB project / code to show a
demo.
Job Description:
We are seeking a talented Vision AI Engineer to join our dynamic team to help
design, develop, and deploy computer vision models for edge-platform
applications. The ideal candidate will have a strong background in computer
vision, deep learning, and AI model optimization, along with a passion for
working on cutting-edge technologies that run on constrained edge devices.
As a Vision AI Engineer, you will be responsible for taking AI-driven
solutions from research to production on edge devices. You will work closely
with other engineering teams to build, optimize, and deploy robust vision
systems that can perform real-time image and video analysis on resource-
constrained platforms.
Key Responsibilities:
Develop and Optimize AI Models: Design and develop computer vision models for
various edge-platforms using deep learning techniques.
Model Optimization: Optimize models for real-time inference on edge devices,
focusing on reducing latency and computational load while maintaining
accuracy.
Embedded Systems Integration: Work closely with embedded systems engineers to
integrate AI models with hardware components.
Edge AI Solutions: Develop algorithms that efficiently leverage edge computing
power for vision-based tasks (e.g., object detection, facial recognition,
activity recognition).
Performance Tuning: Apply techniques such as model quantization, pruning, and
acceleration to enhance model performance on edge devices.
Testing & Validation: Conduct rigorous testing and validation of AI models in
real-world scenarios to ensure robustness and reliability.
Collaboration: Collaborate with cross-functional teams, including software,
hardware, and product engineering teams, to deliver integrated solutions.
Research and Innovation: Stay up-to-date with the latest developments in AI,
machine learning, and computer vision, and contribute to research and
development efforts.
Qualifications:
Education: Ph.D.'s or Master's degree in Computer Science, Electrical
Engineering, AI/ML, or a related field.
Experience:
3+ years of experience in computer vision, deep learning, and AI model
development.
Proven experience with AI frameworks such as TensorFlow, PyTorch, or similar.
Hands-on experience in optimizing models for edge computing platforms (e.g.,
NVIDIA Jetson, Raspberry Pi, mobile devices, Edge-Server Platforms like
Qualcomm Edge Platforms).
Proficiency in programming languages such as Python, C++.
Experience with Kubernetes based Edge Platform, Linux, edge computing
hardware, and real-time applications is a plus.
Skills:
Strong knowledge of computer vision algorithms (e.g., object detection, image
classification, segmentation, etc.).
Experience in AI model deployment and optimization on edge devices.
Knowledge of tools and techniques for model compression (e.g., quantization,
pruning, etc.).
Familiarity with tools for performance profiling and optimization (e.g.,
TensorRT, OpenVINO, etc.).
Experience with cloud technologies and frameworks for model training is a
plus.
Preferred Qualifications:
Experience working in autonomous systems or robotics.
Familiarity with edge AI platforms and deployment tools.
Knowledge of hardware acceleration frameworks (e.g., CUDA, OpenCL).
What We Offer:
Competitive salary and benefits package, Startup Stock Options
Opportunity to work on groundbreaking technologies and cutting-edge AI/Edge
solutions.
Collaborative and inclusive work environment.
Opportunities for growth, development, and learning in a rapidly evolving
field.
Flexible work environment (remote work options available).