#ml
SOFTONIC LLC is looking for Senior Machine Learning Engineer (Computer Vision and Edge AI) for US-based project
Role Overview:
The Senior Machine Learning Engineer will lead the development of computer vision algorithms and machine learning models for real-time event detection on edge devices. This role requires expertise in deep learning, computer vision, and optimization of models for deployment on Linux-based gateways with resource constraints.
Key Responsibilities:
Model Development: Design and implement machine learning models for features such as distracted driving detection, fatigue analysis, lane departure warning, and tailgating detection.
Computer Vision: Develop algorithms for image and video processing using data from cameras.
Edge AI Optimization: Optimize models for real-time inference on edge devices with limited computational resources.
Data Management: Collaborate on data collection strategies, including dataset preparation, annotation, and augmentation.
Testing and Validation: Conduct rigorous testing of models to ensure high accuracy and low latency in real-world conditions.
Collaboration: Work closely with the embedded systems engineer to integrate AI models with hardware components.
Documentation: Maintain comprehensive documentation of model architectures, training processes, and deployment procedures.
Mentorship: Provide guidance and mentorship to junior team members (if applicable).
Required Qualifications:
Experience: Minimum of 5 years of industry experience in developing machine learning models for computer vision applications.
Technical Skills:
Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, and OpenCV.
Programming Languages: Strong programming skills in Python and C++.
Edge AI Deployment: Experience with deploying models on edge devices using TensorFlow Lite, PyTorch Mobile, or similar.
Model Optimization: Knowledge of techniques like quantization, pruning, and knowledge distillation.
Hardware Acceleration: Familiarity with GPUs, NVIDIA Jetson platforms, Intel Movidius, or similar hardware accelerators.
Linux Systems: Proficient in developing and deploying applications on Linux OS.
Domain Knowledge:
Computer Vision: Expertise in CNNs, object detection, semantic segmentation, and video analytics.
Real-Time Processing: Experience with low-latency systems and performance optimization.
Soft Skills:
Problem-Solving: Strong analytical skills to tackle complex technical challenges.
Communication: Excellent verbal and written communication skills.
Team Collaboration: Ability to work effectively in a cross-functional team environment.
Additional Qualifications:
Industry Experience: Experience in the automotive, transportation, or safety systems industry is highly desirable.
Responsibilities Summary
Lead AI model development for computer vision tasks.
Optimize and deploy models on Linux-based gateways.
Collaborate with hardware and software teams for seamless integration.
Ensure compliance with data privacy and industry regulations.
Mentor and guide other team members as needed.
Team Collaboration
Interdisciplinary Work: Ability to work closely with software engineers, hardware engineers, and product managers.
Agile Methodologies: Experience with agile development processes and tools like Jira.
Version Control: Proficient in using Git for code collaboration.
Salary: from 20 mln to 35 mln UZS
Office location: near the Shakhristan metro station, Tashkent
Tel: +998 (77) 706 00 77
TG: @softonic_uzbekistan
👉 Подписаться на канал @UzDev_Jobs
SOFTONIC LLC is looking for Senior Machine Learning Engineer (Computer Vision and Edge AI) for US-based project
Role Overview:
The Senior Machine Learning Engineer will lead the development of computer vision algorithms and machine learning models for real-time event detection on edge devices. This role requires expertise in deep learning, computer vision, and optimization of models for deployment on Linux-based gateways with resource constraints.
Key Responsibilities:
Model Development: Design and implement machine learning models for features such as distracted driving detection, fatigue analysis, lane departure warning, and tailgating detection.
Computer Vision: Develop algorithms for image and video processing using data from cameras.
Edge AI Optimization: Optimize models for real-time inference on edge devices with limited computational resources.
Data Management: Collaborate on data collection strategies, including dataset preparation, annotation, and augmentation.
Testing and Validation: Conduct rigorous testing of models to ensure high accuracy and low latency in real-world conditions.
Collaboration: Work closely with the embedded systems engineer to integrate AI models with hardware components.
Documentation: Maintain comprehensive documentation of model architectures, training processes, and deployment procedures.
Mentorship: Provide guidance and mentorship to junior team members (if applicable).
Required Qualifications:
Experience: Minimum of 5 years of industry experience in developing machine learning models for computer vision applications.
Technical Skills:
Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, and OpenCV.
Programming Languages: Strong programming skills in Python and C++.
Edge AI Deployment: Experience with deploying models on edge devices using TensorFlow Lite, PyTorch Mobile, or similar.
Model Optimization: Knowledge of techniques like quantization, pruning, and knowledge distillation.
Hardware Acceleration: Familiarity with GPUs, NVIDIA Jetson platforms, Intel Movidius, or similar hardware accelerators.
Linux Systems: Proficient in developing and deploying applications on Linux OS.
Domain Knowledge:
Computer Vision: Expertise in CNNs, object detection, semantic segmentation, and video analytics.
Real-Time Processing: Experience with low-latency systems and performance optimization.
Soft Skills:
Problem-Solving: Strong analytical skills to tackle complex technical challenges.
Communication: Excellent verbal and written communication skills.
Team Collaboration: Ability to work effectively in a cross-functional team environment.
Additional Qualifications:
Industry Experience: Experience in the automotive, transportation, or safety systems industry is highly desirable.
Responsibilities Summary
Lead AI model development for computer vision tasks.
Optimize and deploy models on Linux-based gateways.
Collaborate with hardware and software teams for seamless integration.
Ensure compliance with data privacy and industry regulations.
Mentor and guide other team members as needed.
Team Collaboration
Interdisciplinary Work: Ability to work closely with software engineers, hardware engineers, and product managers.
Agile Methodologies: Experience with agile development processes and tools like Jira.
Version Control: Proficient in using Git for code collaboration.
Salary: from 20 mln to 35 mln UZS
Office location: near the Shakhristan metro station, Tashkent
Tel: +998 (77) 706 00 77
TG: @softonic_uzbekistan
👉 Подписаться на канал @UzDev_Jobs