Sr. AI Research Assistant

As an AI Research Specialist at a Pune-based startup, your main role will be to conduct comprehensive research on emerging AI models, analyze their potential integration with the existing system, and offer expert advice on optimizing model performance. Key Responsibilities: - Monitor and analyze new AI models entering the market. - Assess the applicability of emerging models to the AI agent system. - Provide insights on model architectures, weights, biases, and training methods. - Develop and recommend fine-tuning strategies for optimal performance. - Optimize model efficiency by determining the minimal necessary layer structure. Required Qualifications: - Hold an advanced degree in Computer Science (MS or PhD), Machine Learning, Engineering, Applied Mathematics, or related quantitative field. Candidates with backgrounds in Control Theory, Information Theory, or similar disciplines are particularly encouraged to apply. - Possess extensive knowledge of various AI model architectures and their inner workings. - Demonstrate a strong understanding of neural network fundamentals, including weights, biases, and activation functions. - Have experience with model fine-tuning and hyperparameter optimization. - Proficient in Python and common ML frameworks (e.g., TensorFlow, PyTorch). - Be familiar with state-of-the-art AI research and have the ability to quickly grasp new concepts. - Demonstrate the ability to apply systematic, logical thinking to complex problems, particularly in model optimization and efficiency. - Possess excellent analytical and problem-solving skills. - Strong communication skills to convey complex technical concepts clearly. Preferred Skills: - Knowledge of Control Theory concepts (e.g., feedback systems, stability analysis). - Familiarity with Information Theory principles. As an AI Research Specialist at a Pune-based startup, your main role will be to conduct comprehensive research on emerging AI models, analyze their potential integration with the existing system, and offer expert advice on optimizing model performance. Key Responsibilities: - Monitor and analyze new AI models entering the market. - Assess the applicability of emerging models to the AI agent system. - Provide insights on model architectures, weights, biases, and training methods. - Develop and recommend fine-tuning strategies for optimal performance. - Optimize model efficiency by determining the minimal necessary layer structure. Required Qualifications: - Hold an advanced degree in Computer Science (MS or PhD), Machine Learning, Engineering, Applied Mathematics, or related quantitative field. Candidates with backgrounds in Control Theory, Information Theory, or similar disciplines are particularly encouraged to apply. - Possess extensive knowledge of various AI model architectures and their inner workings. - Demonstrate a strong understanding of neural network fundamentals, including weights, biases, and activation functions. - Have experience with model fine-tuning and hyperparameter optimization. - Proficient in Python and common ML frameworks (e.g., TensorFlow, PyTorch). - Be familiar with state-of-the-art AI research and have the ability to quickly grasp new concepts. - Demonstrate the ability to apply systematic, logical thinking to complex problems, particularly in model optimization and efficiency. - Possess excellent analytical and problem-solving skills. - Strong communication skills to convey complex technical concepts clearly. Preferred Skills: - Knowledge of Control Theory concepts (e.g., feedback systems, stability analysis). - Familiarity with Information Theory principles.