Innovation Engineer

As an Innovation Engineer in our team, you will play a crucial role in developing cutting-edge software solutions tailored for math and science education. Your expertise in algorithms, computational science, and mathematics will drive the creation of innovative tools to enhance learning experiences. You will be responsible for developing, optimizing, and maintaining algorithmic solutions to tackle mathematical and scientific challenges. Your role will involve designing software that generates diverse and complex math and science question sets to support various educational curricula. Collaborating closely with educators and subject matter experts, you will translate learning objectives into computational logic and software features. Integrating numeric, symbolic, and computational methodologies, you will create efficient educational tools that facilitate transparent and effective learning experiences. Your work will also involve evaluating and implementing AI/LLM-based modules where they enhance algorithmic approaches, particularly for tasks like natural-language parsing or automated explanation, while critically assessing their performance and limitations. To qualify for this role, you should hold a Bachelor's or Master's degree in Mathematics, Computational Science, Computer Science, Engineering, or a related quantitative field. Additionally, you should have a minimum of 3 years of hands-on experience in computational roles focused on algorithm development, symbolic/numeric computation, or mathematical modeling. Proficiency in programming languages such as Python, C++, Java, or similar languages, along with experience in computation-focused libraries like NumPy, SymPy, SageMath, MATLAB, or Mathematica, is essential. Preferred qualifications include experience in developing educational software involving symbolic/numerical computation or complex algorithmic logic, as well as an understanding of modern AI tools and their applications in math and science problem solving. You should possess the ability to judiciously integrate LLMs or AI-based modules for specific tasks where algorithmic solutions may be impractical. Key skills for success in this role include analytical and logical reasoning abilities for mathematical modeling and software design, a genuine passion for leveraging technology to advance math and science education, effective communication skills for cross-functional collaboration, and awareness of recent advancements in computational math and AI approaches to strategically apply them where they offer distinct value.,