AI Functional Lead

Job Summary

The main purpose of the position is to drive innovation in artificial intelligence by creating robust, efficient, scalable neural network solutions, and involves studying and applying functional principles of neural networks to ensure optimal performance. This position also include collecting, interpreting, and analyzing data to enhance model learning processes, as well as designing algorithms and rigorous testing procedures to identify and address potential flaws and anomalies.

Key Responsibilities

• Requirement Analysis and Problem Definition, Oversee the process of defining project goals and technical requirements to ensure alignment with business needs and objectives for neural network solutions.
• Data Collection and Preprocessing, Oversee data gathering and preprocessing processes to ensure alignment with project standards and timely completion of deliverables.
• Model Architecture Design, Review and approve final neural network architecture designs, ensuring they align with overall project goals.
• Algorithm Development and Implementation, Oversee the development and integration of algorithms, ensuring alignment with system architecture and performance goals.
• Model Training and Validation, Oversee model training processes, ensure model quality and reliability, and verify that validation procedures align with project standards.
• Deployment and Integration, Oversee the deployment and operational integration of neural network solutions to ensure alignment with business systems and objectives.
• Performance Monitoring and Continuous Improvement, Oversee continuous improvement initiatives for neural network systems and ensure that performance targets are consistently achieved.
• Leveraging expertise in statistical analysis, big data processing, distributed systems, and related fields to implement and deploy practical solutions.

Qualification:

• Minimum 10+ years of hands-on experience in designing, developing, and deploying artificial neural network models in a high-tech or R&D environment.
• Bachelor or Master in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field with a focus on neural networks and deep learning.
• Preferred specialized coursework or research in Artificial Neural Networks (ANN), Deep Learning, Computational Neuroscience, or Bio-inspired AI.
• Certifications in AI/ML frameworks (e.g., TensorFlow, PyTorch) or cloud-based AI deployment (AWS, GCP, Azure).
• Proven track record in leading AI/ML projects from concept to deployment, including algorithm development, model optimization, and performance tuning.
• Strong expertise in statistical analysis, big data processing, and distributed computing frameworks (e.g., Spark, Hadoop).
• Experience with large-scale neural network training, reinforcement learning, or biologically inspired AI models.
• Demonstrated ability in technical project management, ensuring alignment with business objectives and timelines.
• Experience in applying neural networks to real-world industry problems (e.g., robotics, autonomous systems, healthcare, finance).
• Prior work in research operations, technical product development, or AI innovation labs.
• Familiarity with edge AI deployment, neuromorphic computing, or spiking neural networks (SNNs).
• Experience in mentoring or leading cross-functional AI/ML teams.