Senior Machine Learning Scientist

Senior Machine Learning Scientist - Applied Research (USA Remote) Job Type: Full-time Overview When you join Turnitin, you'll be welcomed into a company that is a recognized innovator in the global education space. For over 25 years, Turnitin has partnered with educational institutions to promote honesty, consistency, and fairness across all subject areas and assessment types. Over 21,000 academic institutions, publishers, and corporations use our services: Feedback Studio, Originality, Gradescope, ExamSoft, Similarity, and iThenticate. Experience a remote-centric culture that empowers you to work with purpose and accountability in a way that best suits you, supported by a comprehensive package that prioritizes your overall well-being. Our diverse community of colleagues are all unified by a shared desire to make a difference in education. Turnitin is a global organization with team members in over 35 countries including the United States, Mexico, United Kingdom, Australia, Japan, India, and the Philippines. Turnitin, LLC is an equal opportunity employer- vets/disabled. Responsibilities Machine Learning is integral to the continued success of our company. Our product roadmap is exciting and ambitious. You will join a global team of curious, helpful, and independent scientists and engineers, united by a commitment to deliver cutting-edge, well-engineered Machine Learning systems. You will work closely with product and engineering teams across Turnitin to integrate Machine Learning into a broad suite of learning, teaching and integrity products. We are in a unique position to deliver Machine Learning used by hundreds of thousands of instructors teaching millions of students around the world. Your contributions will have global reach and scale. Billions of papers have been submitted to the Turnitin platform, and hundreds of millions of answers have been graded on the Gradescope and Examsoft platforms. Machine Learning powers our AI Writing detection system, gives automated feedback on student writing, investigates authorship of student writing, revolutionizes the creation and grading of assessments, and plays a critical role in many back-end processes. Day-to-day, your responsibilities are to: Research and develop production grade Machine Learning models as described above. Optimize models for scaled production usage. Work with colleagues in the AI team, other Engineering teams, subject matter experts, Product Management, Marketing, Sales and Customer support to explore ongoing product issues, challenges and opportunities and then recommend innovative ML/AI based solutions. Help out with ad-hoc one-off tasks as a team player within the AI team. Work with subject matter experts to curate and generate optimal datasets following responsible data collection and model maintenance practices. Explore and access SQL, no-SQL and web data and write efficient parallel pipelines. Review and design datasets to ensure data quality. Investigate weaknesses of models in production and work on pragmatic solutions. Utilize, adopt, and fine-tune off-the shelf models, including LLMs exposed via API (through prompt engineering and agents) and locally hosting LMs and other foundation models. Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. Write clean, efficient, and modular code with automated tests and appropriate documentation. Stay up to date with technology and platforms, make good technological choices, and be able to explain them to the organization. Work with downstream teams to productionize your work and ensure that it makes into a product release. Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners. Present and publish your work. Qualifications Required Qualifications: 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. At least 5 years of industry experience in Machine / Deep Learning (we use the python ecosystem for ML), Computer Science and Software Engineering. A strong understanding of the math and theory behind machine learning and deep learning is a prerequisite. 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. Excellent communication and teamwork skills. Fluent in written and spoken English. Would be a plus We’re an applied science group, therefore Software development proficiency is a requirement. Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus. A Computer Science educational background is preferred as opposed to statistics or pure mathematics. Experience with advanced prompting / agentic-systems and fine-tuning or training an LLM, using industry accepted platforms. Showcase previous work (e.g. via a website, presentation, open source code). Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries. The expected annual base salary range for this position is: $111,000/year to $185,000/year. This position is bonus eligible / commission-based. As a Remote-First company, actual compensation will be provided in writing at the time of offer, if extended, and is determined by work location and a range of other relevant factors, including but not limited to: experience, skills, degrees, licensures, certifications, and other job-related factors. Internal equity, market and organizational factors are also considered. Total Rewards Turnitin maintains a Total Rewards package that is competitive within the local job market. Beyond regular pay plus bonus or commission, Turnitin offers generous time off and health and wellness programs that provide choice and flexibility and a safety net for life's challenges. This includes a remote-centric culture and a comprehensive package prioritizing well-being. Our Mission and Values Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes. Our Values underpin everything we do. Customer Centric - We put educators and learners at the center of everything we do to ensure integrity and improve learning outcomes. Passion for Learning - We seek teammates who are constantly learning and growing. Integrity - The heartbeat of Turnitin, shaping our products and how we work with customers and vendors. Action & Ownership - A bias toward action and empowerment to make decisions. One Team - Collaboration across teams and celebrating successes. Global Mindset - Respect for local cultures and diversity, thinking globally and acting locally. Remote First Culture Health Care Coverage* Education Reimbursement* Competitive Paid Time Off 4 Self-Care Days per year National Holidays* Charitable contribution match* Monthly Wellness or Home Office Reimbursement* Access to Modern Health (mental health platform) Retirement Plan with match/contribution* * varies by country EEO and Inclusion Seeing Beyond the Job Ad At Turnitin, we recognize it’s unrealistic for candidates to fulfill 100% of the criteria in a job ad. 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 evolve alongside us, join our team Turnitin, LLC is committed to the policy that all persons have equal access to its programs, facilities and employment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. #J-18808-Ljbffr