Join our AI Research team to develop cutting-edge deep learning models that power our Xyranik AI Agentic platform. You'll work on neural network architectures for autonomous decision-making, natural language processing, and computer vision applications that enable AI agents to understand and interact with complex environments.
Responsibilities
Design and implement state-of-the-art deep learning models for AI agents
Develop neural network architectures for autonomous decision-making systems
Optimize model performance for real-time AI agent applications
Research and implement novel deep learning techniques for agentic AI
Collaborate with engineering teams to deploy models in production
Requirements
Master's or PhD in Computer Science, Machine Learning, or related field
3+ years of experience in deep learning research or applications
Robust proficiency in Python and deep learning frameworks (TensorFlow, PyTorch)
Extensive knowledge of neural network architectures (CNNs, RNNs, Transformers)
Experience with GPU acceleration and distributed training
Published research or demonstrable projects in deep learning
Preferred Qualifications
Experience with reinforcement learning and agent-based systems
Knowledge of large language models and their applications
Background in computer vision or natural language processing
Experience with model deployment and MLOps practices
About FactoFlare
FactoFlare is a leading AI technology company focused on developing intelligent solutions that help businesses streamline operations, enhance productivity, and drive innovation. We are committed to creating a diverse, inclusive workplace where all employees can thrive and contribute to our mission of making advanced AI technology accessible and beneficial to organizations of all sizes.
We offer competitive compensation, comprehensive
📌 Deep Learning Engineer (Bengaluru)
🏢 FactoFlare AI
📍 Bengaluru
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