Senior Machine Learning Scientist - Applied Research (USA Remote)

Senior Machine Learning Scientist - Applied Research (USA Remote)

Employment Type : Full-time

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.

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.

Responsibilities

We’re an applied science group leaning towards modern Deep Learning. 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. You will focus on developing novel and deployable ML models and solutions where no ready-made solution may be available. Therefore you need to be conversant enough with the mathematics of machine learning and deep neural networks such that you can construct novel model architectures, loss functions, training methods, training loops etc. You are also expected to keep abreast of the latest research advancements in AI and Deep Learning across modalities and apply those to your work. While we leverage ready-made training platforms, we also write our own training loops. Additionally, the models need to be directly deployable in our products, therefore, production level coding and software engineering proficiency is required. You may train large models (up to 100s of billions of parameters) therefore, ability to train on multiple GPUs and nodes and knowledge of the latest model training and inferencing advancements is necessary. Next, the models must perform well in production not only in terms of accuracy but also compute-cost. Delivering such software requires a sufficiently deep Computer Science background. Dataset exploration, generation (synthetic), design, construction and analysis, are a routine part of the job and may occupy a significant fraction of your time. Also, datasets can be large (billions of samples), therefore the ability to write parallel and efficient pipelines is a necessary skill. You will also be involved in code & model maintenance, code hardening (preparing the model and code for production pipelines), developing and staging demos and presenting your work within the company as well as via publications in peer reviewed venues (preferably A / A+ rated).

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.

Required Qualifications :

Would be a plus :

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

Turnitin maintains a Total Rewards package that is competitive within the local job market. This includes generous time off and health and wellness programs, a remote-centric culture, and a comprehensive package prioritizing well-being.

Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes.

Our Values underpin everything we do.

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.

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