AI Model Training Engineer-Python, Java, C++

1.Data Collection and Preparation:
Collect, curate, and annotate large datasets for training AI models.
Ensure data quality and integrity through preprocessing and cleaning.
2. Model Development and Training:
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.