Turnitin · 2 hours ago
Senior Machine Learning Scientist - Applied Research (USA Remote)
United States
Full-time
Remote
Mid, Senior Level
$111K/yr - $185K/yr
5+ years expTurnitin is a recognized innovator in the global education space, seeking a Senior Machine Learning Scientist to join their applied science group. The role involves developing production-grade machine learning models, collaborating with various teams to integrate machine learning into educational products, and maintaining high standards of model performance and code quality.
E-LearningEducationSoftware
Responsibilities
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
Qualification
Required
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
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.)
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
Preferred
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
Familiarity in building front-ends (Gradio, Streamlit, Dash or more standard React, Javascript, Flask) for simple demos, POCs and prototypes
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
Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda)
Benefits
Remote First Culture
Health Care Coverage
Education Reimbursement
Competitive Paid Time Off
4 Self-Care Days per year
National Holidays
2 Founder Days + Juneteenth Observed
Paid Volunteer Time
Charitable contribution match
Monthly Wellness or Home Office Reimbursement
Access to Modern Health (mental health platform)
Parental Leave
Retirement Plan with match/contribution
Company
Turnitin
Academic integrity starts here.
501-1000 employees
H1B Sponsorship
Turnitin has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (4)
2024 (4)
2023 (3)
2022 (3)
2021 (6)
Funding
Current Stage
Late StageTotal Funding
unknown2019-03-06Acquired
Leadership Team
Chris Caren
CEO
Iana Mykhailenko
Director Of Engineering
Recent News
2025-11-14
2025-10-22
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