The Senior Machine Learning Scientist at Turnitin, LLC will play a key role in developing and maintaining machine learning systems that power Turnitin's suite of educational integrity and learning products. This position involves close collaboration with product, engineering, and subject matter experts to build scalable, production-ready ML solutions with global impact.
What You'll Do
- Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered.
- Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices.
- Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
- Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
- Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs.
- Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings.
- Optimize models for scaled production usage.
- Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners.
- Write clean, efficient, and modular code, with automated tests and appropriate documentation.
- Stay up to date with technology, make good technological choices, and be able to explain them to the organization.
What We're Looking For
- Versatile skill set with a well-balanced combination of research, model training, and production engineering capabilities.
- Experience in model training and maintenance with significant capacity for research, including developing novel model architectures.
- Experience in dataset construction, including data curation, generation, and annotation.
- Experience in model hardening — preparing models and code for production pipelines.
- Ability to work with subject matter experts to define and answer data-driven questions.
- Proficiency in using SQL and scripting languages to extract and transform raw data into trainable datasets.
- Experience developing and tuning machine learning models using best practices for dataset selection, architecture, and hyperparameter tuning.
- Experience utilizing, fine-tuning, and orchestrating Language Models, including third-party LLMs and locally hosted models.
- Ability to optimize machine learning models for large-scale production deployment.
- Strong communication skills to explain model behavior, limitations, and insights to technical and non-technical stakeholders.
- Ability to write clean, efficient, modular code with automated testing and documentation.
- Commitment to staying current with advancements in machine learning and language models.
Technical Stack
- SQL
- scripting languages (e.g., Python)
- Language Models (LMs)
- Large Language Models (LLMs)
- prompt engineering
- model orchestration tools
- machine learning frameworks (e.g., TensorFlow, PyTorch)
- data annotation tools
- production ML pipelines
Team & Environment
- Global team
- Cross-functional team of machine learning scientists and engineers
Benefits & Compensation
- Remote-first work culture with equal access to learning and career opportunities for all employees.
- Global recruitment from diverse backgrounds enabled by remote work.
- Opportunity to work on machine learning systems with global reach and scale, impacting millions of students and educators worldwide.
- Access to vast datasets including billions of submitted papers and hundreds of millions of graded answers.
- Work on impactful products such as AI Writing detection, automated feedback systems, authorship investigation, and assessment creation and grading tools.
Work Mode
- Remote-first culture, respects personal choice and local cultures
- Locations: USA (remote), Oakland, Dallas, Pittsburgh, Newcastle (UK), Stockholm (Sweden), Cologne (Germany), Amsterdam (Netherlands)
