Principal Machine Learning Scientist

About the role

Join Turnitin, a global leader in educational integrity and learning solutions. As a Principal Machine Learning Scientist, you will be at the forefront of developing and deploying cutting-edge machine learning models that impact millions of students and instructors worldwide. You will work closely with product and engineering teams, and your contributions will have a global reach and scale. Key missions: Research and develop Machine Learning models, optimize them for scaled production usage, and integrate them into a broad suite of learning, teaching, and integrity products.. Collaborate with colleagues in the AI team, other Engineering teams, and subject matter experts to explore ongoing product issues and recommend innovative ML/AI based solutions.. Stay current in the field by reading research papers, experimenting with new architectures and methods, and sharing your findings with the team. Profile: - A Computer Science educational background is preferred as opposed to statistics or pure mathematics - Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised - Fluent in written and spoken English - At Turnitin, we recognize it’s unrealistic for candidates to fulfill 100% of the criteria in a job ad - We expect our Senior Machine Learning Scientists to have a well-balanced set of skills, both in the Science as well as Software Engineering aspects of (Deep) Machine Learning - A strong understanding of the math and theory behind machine learning and deep learning is a prerequisite - Showcase previous work (e.g. via a website, presentation, open source code) - Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field or outstanding previous achievements demonstrating excellence in Deep Machine Learning, Computer Science and Software Engineering - Experience with deep learning in other modalities such as vision and speech would be a strong bonus - Interpretability of deep neural networks - Reinforcement learning - Machine / Deep Learning development skills, including popular platforms (we use AWS SageMaker, Hugging Face, Transformers, PyTorch, PyTorch Lightning, Ray, scikit-learn, Jupyter, Weights & Biases etc.) - Experience with advanced prompting / agentic-systems and fine-tuning or training an LLM, using industry accepted platforms - Academic publications in peer reviewed conferences or journals related to Machine Learning - preferably A/A+ rated such as NeurIPS, ICML, ICLR, AAAI, TMLR, JMLR, IJCAI, ICANN, KDD, ACL, EMNLP, NAACL, COLING, CVPR, ICCV, ECCV, IEEE etc - An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families - We’re an applied science group (vs fundamental research), therefore Software development proficiency is a requirement - Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda) - Familiarity in building front-ends (Gradio, Streamlit, Dash or more standard React, Javascript, Flask) for simple demos, POCs and prototypes - Excellent communication and teamwork skills - Familiarity in coding for at-scale production - At least 10 years of industry experience in Machine / Deep Learning (we use the python ecosystem for ML), Computer Science and Software Engineering - We encourage you to apply if you meet the majority of the requirements because we know that skills evolve over time. If you’re willing to learn and unleash your potential alongside us, join our team!