Data Scientist II (Remote, ROU)

Candidates should have at least 2 years of applied machine learning research expertise in developing and deploying production systems. They must be skilled at extracting actionable insights from large, high-dimensional, sparse data across the machine learning pipeline and driving real-world impact. A self-starter with a thirst for new challenges and technologies, candidates should be comfortable with Python, Deep Learning frameworks (e.g., TensorFlow, PyTorch), and cloud technologies in a Linux environment. Expertise in training and fine-tuning LLMs using frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers is required, along with familiarity with GPU-based technologies like CUDA, CuDNN, and TensorRT. An interest in cybersecurity, excellent communication skills to simplify complex concepts, and robust problem-solving and critical-thinking skills are also necessary. A PhD in Computer Science, Statistics, Mathematics, or a related field with a focus on data science, machine learning, or AI, and a track record of research contributions in high-impact, peer-reviewed scientific journals in AI/ML are considered bonus points.