Software Engineer, AI/Machine Learning, PhD, Early Career, 2027 Start

Job description

Collaborate or lead on team projects to carry out design, analysis, and development of advanced ML systems across the stack using your research expertise. Support building end-to-end ML Systems that involves working across the full stack, from low-level hardware acceleration and compiler optimizations to high-level model architecture and production APIs, transforming your research expertise into robust, scalable products. Optimize complex system performance by analyzing and fixing performance bottlenecks, memory inefficiencies, and errors in production systems to meet stringent customer goals. Elevate engineering excellence by writing well-tested code, conducting code reviews and fostering a culture of quality by advocating best engineering practices. Minimum Qualifications: PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience. Experience coding in one of the following programming languages including but not limited to: Python, C, C++, Java, JavaScript or Golang. Experience in Machine Learning or Artificial Intelligence. Preferred Qualifications: Research experience in designing, developing, or applying ML/AI systems or applications in a large-scale distributed environment. Experience in designing, training, or refining complex ML/AI models. Experience in building a stack for an AI-powered application, including data ingestion and processing pipelines, building APIs, and connecting the model to a user-facing interface. Familiarity with model architectures (CNNs, NLP Transformers, Diffusion/Vision Transformers). Experience developing with Rust and modern deep learning frameworks such as PyTorch, JAX, or TensorFlow. Availability to start in a full-time role in 2027.