• Design and implement machine learning models using various algorithms.
• Knowledge to optimized model to fit with low configuration of AI inference machine.
• Knowledge about data augmentation and it benefits to training.
• Train models on prepared datasets and fine-tune parameters to enhance performance.
• Utilize frameworks such as PyTorch, TensorFlow, or Keras for model development.

3.     Performance Evaluation and Optimization:

• Evaluate model performance using metrics like accuracy, precision, recall, and F1 score and knowledge about most of useful SOTA metrics.
• Optimize models for efficiency and performance.
• Conduct experiments to compare different models and approaches.
• Experience in deploying ML/DL applications on specific embedded platforms (e.g., STM32 AI, NVIDIA Jetson, NXP, etc.) is a strong plus
• Debugging skills for embedded targets is a plus
• Experience with RTOS or Linux programming is a plus

4.     Collaboration and Communication:

• Work closely with data scientists, software engineers, and other stakeholders.
• Communicate findings and progress to team members and management.
• Collaborate on integrating AI models into existing systems and applications.
• Knowing system integration is a plus.

5.     Continuous Learning and Improvement:

• Stay updated with the latest advancements in AI and machine learning.
• Capability to read and understand SOTA papers.
• Participate in workshops, conferences, and training sessions.
• Implement new techniques and tools to improve model performance and development processes.

Qualifications:

• Bachelor's Degree: In Computer Science, Data Science, Mathematics, Information Technology, or a related field.
• Programming Languages: Proficiency in Python, Java, C++, and SQL.
• Machine Learning: Strong understanding of machine learning algorithms and techniques.
• Data Analysis: Ability to analyze and interpret large datasets.
• Mathematics: Solid foundation in linear algebra, calculus, and probability.
• Software Development: Knowledge of software engineering principles and practices.
• Problem-Solving: Excellent problem-solving skills and the ability to troubleshoot issues with AI models.
• Communication: Strong communication skills for effective collaboration and reporting
• Edge AI : Knowledge background about efficient AI/edge AI is a plus

Benefits:

• Good salary (includes base salary, additional salary, housing allowance, meal allowance, etc.)
• 13th month salary + Incentive/performance bonus
• Salary review twice a year
• Lunch monthly support
• Mon–Fri & alternative Saturday working schedule with 44 hours/week.
• 12 annual leave days plus 1 birthday leave
• Health care insurance
• Training & career development program
• Oversea working opportunities
• Have opportunities to work on international projects.
• Working in an international environment with experts around the world
• Opportunities for career advancement to Team Leader, Group Leader, and Manager positions
• Monthly budget for team activities, etc.