About the Company: We are a well-funded, rapidly growing, early-stage AI startup headquartered in Silicon Valley that is building a two-sided product - one side meant for global consumers and the other side for AI builders and researchers. We work on the cutting edge of AI across the stack. Check out our product that was launched recently, and how it solves the foundational challenge of robust and trustworthy AI model evaluations. Here's more information about us. Job Summary : We are seeking a highly skilled and motivated Applied AI researcher to join our innovative team. The ideal candidate will have a strong background in modern LLM architectures and applications, and experience in using GenAI approaches in an applied, production environment. Responsibilities Research and track emerging trends in GenAI and LLM advancements to identify potential applications within the company. Design, build, and maintain LLM-based applications and solutions. Optionally manage the full ML lifecycle, including data analysis, preprocessing, model architecture, training, evaluation, and MLOps. Collaborate with product engineers, designers, and data scientists to define and deliver cutting-edge AI solutions. Convey complex technical information clearly to audiences with varying levels of AI expertise. Troubleshoot and debug AI applications to resolve performance and accuracy issues. Write clean, maintainable, and well-documented research and production code. Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. or equivalent experience is a plus). Minimum of 3 years of experience in machine learning, with a track record of deploying AI models in real-world applications. Strong programming skills in Python and familiarity with libraries such as PyTorch, TensorFlow, NumPy, and JAX. Deep understanding of machine learning algorithms, data structures, and model evaluation methods. Excellent communication and presentation skills, with the ability to explain design decisions to both experts and non-experts. Strong analytical skills and ability to work independently and collaboratively in fast-paced environments. Preferred Qualifications Authored or co-authored research papers in reputable AI/ML conferences or impactful technical blog posts. Active participation in open-source AI/ML projects, Kaggle competitions, or similar initiatives. Experience working in startup or small, fast-paced environments.
