What We Are Looking For • A background in Computer Science, Mathematics, Statistics, Artificial Intelligence, or a related field. Both undergraduate and graduate candidates are welcome. • Strong software engineering fundamentals, with practical understanding of development workflows, computer systems, network services, asynchronous programming, and production deployment. • Experience with Python backend development. You should be comfortable building reliable service APIs with frameworks such as FastAPI or Django, and understand API design, logging, testing, and production debugging. • Solid machine learning and deep learning foundations, including linear algebra, calculus, loss design, batch training, efficient fine\-tuning, offline training, and online inference. • Hands\-on ML development experience with PyTorch, TensorFlow, and Hugging Face. Experience with inference and deployment tools such as vLLM or ONNX is a strong plus, especially if you have worked on model loading, acceleration, quantization, or model serving. • Familiarity with cloud and deployment environments such as AWS, Azure, or GCP. Experience with Docker, Linux, CI/CD, or GPU inference services is a plus. • Basic testing discipline, including the ability to write and maintain unit tests, integration tests, and regression tests for long\-term system quality. • Most importantly, we value engineers who genuinely want to build a good product: people who communicate actively when requirements are unclear, propose practical solutions when metrics are hard to define, and write software with long\-term maintainability and scalability in mind.
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