Research Engineer, Intern

As a Research Engineer Intern at Harmonic, your key responsibilities will include developing and optimizing mathematical routines in both Python and C++, leveraging large compute clusters to create synthetic reasoning data, and training and evaluating large language models on mathematical reasoning tasks. You'll also collaborate with fellow researchers to enhance our research initiatives, helping to propel our projects at the intersection of AI and mathematics.

To qualify for the Research Engineer Intern role at Harmonic, candidates should be in the process of obtaining a BS or MS in Computer Science and possess strong programming skills in Python and C++. A good understanding of mathematical concepts such as algebra, geometry, and analysis is also essential. Preferred qualifications include pursuing a PhD in Computer Science, Mathematics, or a related field, alongside experience with distributed computing on SLURM clusters and training large language models.

Harmonic requires Research Engineer Interns to have strong programming skills, particularly in Python and C++. Experience in software development and testing is crucial as you will be tasked with developing mathematical routines and engaging in various computational challenges in a research setting.

At Harmonic, collaboration is at the core of our research and development process. As a Research Engineer Intern, you will work closely with experienced researchers and engineers, engaging in discussions that contribute directly to the advancement of the Harmonic research roadmap. This collaborative spirit ensures a rich learning environment where ideas flow freely and innovation thrives.

Harmonic is an exciting, forward-thinking company at the forefront of AI and mathematics. As a Research Engineer Intern, you'll get to work with cutting-edge technology in a vibrant, supportive team environment. We're committed to diversity and creating an inclusive atmosphere where every employee can thrive and contribute to groundbreaking discoveries.

In your response, highlight projects or courses where you utilized Python and C++ for mathematical computations. Discuss specific algorithms or processes you implemented and how they solved a problem, showcasing both your coding expertise and your mathematical understanding.

Explain your understanding of key concepts in training language models, such as data preprocessing, model selection, and evaluation metrics. Share experiences you've had with similar tasks and emphasize your ability to adapt and learn quickly in this area.

Reflect on your favorite areas in mathematics, such as algebra, geometry, or calculus. Discuss how these concepts relate to AI and your insights into their importance in computational contexts, demonstrating your passion for the subject matter.

Share a relevant example, focusing on the specific challenge you encountered, the steps you took to address it, and the outcome. This question allows you to showcase not just your problem-solving skills but also your resilience and critical thinking.

Discuss techniques for improving code efficiency, such as code profiling, employing appropriate data structures, or algorithm optimization. You can mention specific library tools or methodologies you've used in past projects to make your point more compelling.

Detail your approach to data analysis, including any statistical methods or tools you employ. Explain how you validate the quality and relevance of the generated data for your intended reasoning tasks.

In your response, focus on the project specifics, your role, and the technologies used. Discuss the challenges of distributed systems and how you tackled them, emphasizing your knowledge of SLURM or other cluster management solutions.

Express your enthusiasm for the convergence of these two fields. Discuss how you envision leveraging AI to solve complex mathematical problems or vice versa, showcasing your visionary perspective and understanding of current trends.

Share your resources for staying informed, such as academic journals, conferences, or online courses. Discuss your proactive approach to learning and how you apply this knowledge practically in your field.

Highlight why Harmonic excites you. Discuss their mission, the innovative projects, and the opportunity to work with expert researchers. Emphasize alignment with your own interests in mathematics and AI, underlining your eagerness to contribute to their groundbreaking work.