Senior Machine Learning Scientist

Join Turnitin as a Senior Machine Learning Scientist and contribute to cutting-edge educational technologies by developing advanced ML models and systems remotely.

Responsibilities: Focus on model training, dataset construction, and machine learning model development, collaborating with product and engineering teams to integrate ML into educational products.

Responsibilities:

Skills: Expertise in machine learning and deep learning, strong programming skills in Python, experience with data handling and analysis, and proficiency in working with various ML frameworks.

Skills:

Qualifications: Master's or PhD in Computer Science, AI, or related field with at least 8 years of software engineering experience, along with familiarity in developing deep learning models.

Qualifications:

Location: Remote in the USA

Location:

Compensation: $111000 - $185000 / Annually

Compensation:

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 and Requirements:

Responsibilities and Requirements:

Responsibilities and Requirements:

Responsibilities and Requirements:

We expect Senior Machine Learning Scientists to be versatile and have a well-balanced set of skills. You will focus on model training and maintenance with significant capacity for research (developing novel model architectures), dataset construction, and model hardening (preparing the model and code for production pipelines).

Day-to-day, your responsibilities are to:

Day-to-day, your responsibilities are to:

Day-to-day, your responsibilities are to:

Day-to-day, your responsibilities are to:

• 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.

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.

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.

Required Qualifications:

Required Qualifications:

Required Qualifications:

Required Qualifications:

• 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 strong understanding of the math and theory behind machine learning and deep learning.
• Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
• Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).
• An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.
• Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.
• Excellent communication and teamwork skills.
• Fluent in written and spoken English.

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 strong understanding of the math and theory behind machine learning and deep learning.

Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).

Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).

An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.

Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.

Excellent communication and teamwork skills.

Fluent in written and spoken English.

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 strong understanding of the math and theory behind machine learning and deep learning.

Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).

Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).

An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.

Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.

Excellent communication and teamwork skills.

Fluent in written and spoken English.

Would be a plus:

Would be a plus:

Would be a plus:

Would be a plus:

• 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).
• Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes.  
• Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai).
• 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).

Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes.  

Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai).

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).

Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes.  

Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai).

Showcase previous work (e.g. via a website, presentation, open source code).

The expected annual base salary range for this position is: $111,000/year to $185,000/year. This position is bonus eligible / commission-based.

The expected annual base salary range $111,000/year to $185,000/year.

The expected annual base salary range $111,000/year to $185,000/year.

The expected annual base salary range $111,000/year to $185,000/year.

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

Total Rewards @ Turnitin

Turnitin maintains a Total Rewards package that is competitive within the local job market. People tend to think about their Total Rewards monetarily — solely as regular pay plus bonus or commission. This is what they earn in exchange for what they do. However, Turnitin delivers more than just these components. Beyond the intrinsic rewards of unleashing your potential to positively impact global education, and thriving in an organization that is free of politics and full of humble, inclusive and collaborative teammates, the extrinsic rewards at Turnitin include generous time off and health and wellness programs that offer choice and flexibility and provide a safety net for the challenges that life presents from time to time. 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.

Total Rewards @ Turnitin

Total Rewards @ Turnitin

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

Our Mission

Our Values underpin everything we do.

Our Values

Our Mission Our Values

Our Mission Our Values

• Customer Centric - We realize our mission to ensure integrity and improve learning outcomes by putting educators and learners at the center of everything we do.
• Passion for Learning - We seek out teammates that are constantly learning and growing and build a workplace which enables them to do so.
• Integrity - We believe integrity is the heartbeat of Turnitin. It shapes our products, the way we treat each other, and how we work with our customers and vendors.
• Action & Ownership - We have a bias toward action and empower teammates to make decisions.
• One Team - We strive to break down silos, collaborate effectively, and celebrate each other’s successes.
• Global Mindset - We respect local cultures and embrace diversity. We think globally and act locally to maximize our impact on education.

Customer Centric - We realize our mission to ensure integrity and improve learning outcomes by putting educators and learners at the center of everything we do.

Customer Centric

Passion for Learning - We seek out teammates that are constantly learning and growing and build a workplace which enables them to do so.

Passion for Learning

Integrity - We believe integrity is the heartbeat of Turnitin. It shapes our products, the way we treat each other, and how we work with our customers and vendors.

Integrity

Action & Ownership - We have a bias toward action and empower teammates to make decisions.

Action & Ownership

One Team - We strive to break down silos, collaborate effectively, and celebrate each other’s successes.

One Team

Global Mindset - We respect local cultures and embrace diversity. We think globally and act locally to maximize our impact on education.

Global Mindset

Customer Centric - We realize our mission to ensure integrity and improve learning outcomes by putting educators and learners at the center of everything we do.

Customer Centric

Customer Centric

Customer Centric

Passion for Learning - We seek out teammates that are constantly learning and growing and build a workplace which enables them to do so.

Passion for Learning

Passion for Learning

Passion for Learning

Integrity - We believe integrity is the heartbeat of Turnitin. It shapes our products, the way we treat each other, and how we work with our customers and vendors.

Integrity

Integrity

Integrity

Action & Ownership - We have a bias toward action and empower teammates to make decisions.

Action & Ownership

Action & Ownership

Action & Ownership

One Team - We strive to break down silos, collaborate effectively, and celebrate each other’s successes.

One Team

One Team

One Team

Global Mindset - We respect local cultures and embrace diversity. We think globally and act locally to maximize our impact on education.

Global Mindset

Global Mindset

Global Mindset

Global Benefits

Global Benefits

Global Benefits

Global 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*

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*

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*

* varies by country

Seeing Beyond the Job Ad

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.

Seeing Beyond the Job Ad

Seeing Beyond the Job Ad