AI Research Scientist

<h3>📋 Description</h3> • The AI Research Scientist will be responsible for conducting cutting-edge research in artificial intelligence, machine learning, and related fields to advance the organization’s technological capabilities. • This role involves developing innovative algorithms, experimenting with new AI techniques, and contributing to academic and industry knowledge. • Key Responsibilities: Research & Innovation: Conduct advanced research in AI and machine learning, focusing on developing new algorithms, models, and techniques to solve complex problems. • Conducts cutting-edge research in AI and develops innovative algorithms and solutions. • Algorithm Design: Design, implement, and evaluate AI algorithms in areas such as natural language processing (NLP), computer vision, reinforcement learning, and deep learning. • Experimentation: Design and conduct experiments to validate hypotheses, optimize models, and assess the effectiveness of new methods. • Publications: Contribute to the AI community by publishing research papers, attending conferences, and presenting findings in academic and industry settings. • Collaboration: Collaborate with other researchers, data scientists, and software engineers to integrate new AI technologies into the company’s products and services. • Prototyping: Develop prototypes and proof-of-concept models that demonstrate the potential of new AI technologies. • Mentorship: Provide guidance and mentorship to junior researchers, data scientists, and machine learning engineers. • Data Collection & Analysis: Work with data engineers and scientists to collect, preprocess, and analyze large datasets for AI model training and validation. • Model Evaluation: Develop evaluation frameworks to assess the performance and efficiency of AI models, ensuring their robustness and scalability. • Technology Transfer: Work with product teams to translate research innovations into deployable technologies for real-world applications. <h3>🎯 Requirements</h3> • Education: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • Experience: Proven research experience in AI, machine learning, or deep learning (3+ years preferred). • Strong publication record in AI-related conferences and journals (e.g., NeurIPS, ICML, CVPR, ACL). • Hands-on experience with machine learning frameworks and tools such as TensorFlow, PyTorch, or Keras. • Experience with algorithm development in areas like deep learning, reinforcement learning, or computer vision. • Proficiency in programming languages such as Python, C++, or Java. • Skills: Strong theoretical understanding of AI and machine learning algorithms. • Familiarity with mathematical modeling, statistics, and optimization techniques. • Knowledge of cloud platforms (AWS, Azure, GCP) for large-scale experiments. • Excellent problem-solving skills and critical thinking. • Ability to work independently on long-term research projects while also collaborating with cross-functional teams. • Strong communication skills, with the ability to explain complex technical concepts clearly to different stakeholders. • Preferred Qualifications: Post-doctoral experience or industry research experience in AI. • Experience in applying AI techniques in domains such as healthcare, finance, robotics, or autonomous systems. • Familiarity with big data frameworks (e.g., Hadoop, Spark). • Experience in reinforcement learning, generative models, or neural architecture search. • Demonstrated ability to transition research findings into practical applications.