AI Research Scientist

At WerQ AI, we are at the forefront of AI innovation, dedicated to creating solutions that enhance workplace productivity and efficiency. We are looking for an AI Research Scientist to contribute to our mission by conducting cutting-edge research and developing advanced algorithms in the field of artificial intelligence. In this role, you will leverage your expertise to design, implement, and evaluate new AI models that can be applied to real-world problems in workplace environments. You will collaborate with cross-functional teams to translate your research findings into practical applications, driving the future of AI integration in our products. If you are passionate about pushing the boundaries of AI research and possess a strong analytical mindset, we invite you to join our talented team and help shape the future of work.

Responsibilities

• Conduct innovative research in AI and machine learning, focusing on applications relevant to workplace dynamics.
• Design, develop, and implement algorithms and models that improve AI functionalities and performance.
• Analyze complex datasets to derive insights and validate research hypotheses.
• Collaborate with software engineering teams to integrate research findings into existing and new products.
• Publish research results in academic journals and present findings at conferences to share knowledge within the AI community.
• Stay current with advancements in AI technologies and methodologies, fostering a culture of continuous learning.
• Mentor junior researchers and interns in their research projects and methodologies.

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field; relevant industry experience is a plus.
• 3-5 years of experience in AI research, with a strong focus on machine learning, deep learning, or natural language processing.
• Proficiency in programming languages such as Python, R, or Java and experience with AI frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of algorithms, data structures, and statistical analysis.
• Experience with cloud technologies for model training and deployment (e.g., AWS, Google Cloud).
• Excellent problem-solving and analytical skills, demonstrating creativity in research and application development.
• Strong communication skills, with the ability to clearly articulate complex ideas to both technical and non-technical audiences.