ZipRecruiter
Senior Machine Learning Scientist - Applied Research (USA Remote)
ZipRecruiter, Washington, District of Columbia, us, 20022
Overview
Turnitin is a global organization with a remote-centric culture that supports a comprehensive package prioritizing well-being. Turnitin has partnered with educational institutions for over 25 years and serves over 21,000 academic institutions, publishers, and corporations through products including Feedback Studio, Originality, Gradescope, ExamSoft, Similarity, and iThenticate. Turnitin, LLC is an equal opportunity employer- vets/disabled. Machine Learning is integral to the continued success of our company. You will join a global team of scientists and engineers to deliver cutting-edge ML systems and to integrate ML into a broad suite of learning, teaching and integrity products. The role has global reach, impacting hundreds of thousands of instructors and millions of students around the world. Responsibilities
Research and develop production-grade Machine Learning models and optimize them for scaled production usage. Collaborate with the AI team, other Engineering teams, subject matter experts, Product Management, Marketing, Sales and Customer Support to explore product issues and opportunities and recommend innovative ML/AI-based solutions. Assist with ad-hoc one-off tasks as a team member within the AI team. Curate and generate optimal datasets with responsible data collection and model maintenance practices. Explore SQL, NoSQL and web data and build efficient parallel pipelines. Ensure data quality in dataset design. Investigate weaknesses of models in production and implement pragmatic improvements. Utilize, adopt, and fine-tune off-the-shelf models, including LLMs via API and locally hosting LM and other foundation models. Stay current in the field by reading research papers, experimenting with new architectures and LLMs, and sharing findings. Write clean, efficient, modular code with automated tests and documentation. Keep up to date with technology and platforms, justify technical decisions, and communicate them to the organization. Work with downstream teams to productionize work and ensure it makes it into a product release. Communicate insights, behavior, and limitations of models to peers, subject matter experts, and product owners. Present and publish work as appropriate. Qualifications
Required Qualifications: Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, or outstanding achievements in Deep Machine Learning, Computer Science and Software Engineering. At least 5 years of industry experience in Machine/Deep Learning, CS and Software Engineering using the Python ecosystem for ML. Strong understanding of the math and theory behind machine learning and deep learning. Academic publications in peer-reviewed conferences or journals related to Machine Learning (preferably A/A+ rated such as NeurIPS, ICML, ICLR, AAAI, etc.). Machine/Deep Learning development skills with platforms such as AWS SageMaker, Hugging Face, Transformers, PyTorch, PyTorch Lightning, Ray, scikit-learn, Jupyter, Weights & Biases, etc. Understanding of models, training/fine-tuning, and familiarity with industry-standard LM families. Excellent communication and teamwork skills; fluent in written and spoken English. Would be a plus: Software development proficiency; experience with text data to build ML models; experience with other modalities (vision, speech) is a bonus. Computer Science educational background. Familiarity with front-end tools (Gradio, Streamlit, Dash or React/Javascript/Flask) for demos and prototypes. Experience with advanced prompting/agentic systems and fine-tuning or training an LLM using industry platforms. Showcase previous work (website, presentation, open source code). Experience coding for at-scale production, including back-end APIs or libraries. DevOps skills (Docker, AWS EC2/Batch/Lambda). Additional Information
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 is provided in writing at the time of offer and varies by work location and other factors. Total Rewards @ Turnitin Turnitin maintains a Total Rewards package that is competitive within the local job market, including benefits beyond base pay such as time off and health and wellness programs. Our Mission
is to ensure the integrity of global education and meaningfully improve learning outcomes. Our Values
underpin everything we do. Customer Centric
- Educators and learners are at the center of our work. Passion for Learning
- We seek teammates who are constantly learning and growing. Integrity
- The heartbeat of Turnitin in products and interactions. Action & Ownership
- Bias toward action and empowered decision-making. One Team
- Break down silos and collaborate. Global Mindset
- Respect local cultures and think globally to maximize impact. Global Benefits Remote First Culture Health Care Coverage* Education Reimbursement* Competitive Paid Time Off 4 Self-Care Days per year 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
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Turnitin is a global organization with a remote-centric culture that supports a comprehensive package prioritizing well-being. Turnitin has partnered with educational institutions for over 25 years and serves over 21,000 academic institutions, publishers, and corporations through products including Feedback Studio, Originality, Gradescope, ExamSoft, Similarity, and iThenticate. Turnitin, LLC is an equal opportunity employer- vets/disabled. Machine Learning is integral to the continued success of our company. You will join a global team of scientists and engineers to deliver cutting-edge ML systems and to integrate ML into a broad suite of learning, teaching and integrity products. The role has global reach, impacting hundreds of thousands of instructors and millions of students around the world. Responsibilities
Research and develop production-grade Machine Learning models and optimize them for scaled production usage. Collaborate with the AI team, other Engineering teams, subject matter experts, Product Management, Marketing, Sales and Customer Support to explore product issues and opportunities and recommend innovative ML/AI-based solutions. Assist with ad-hoc one-off tasks as a team member within the AI team. Curate and generate optimal datasets with responsible data collection and model maintenance practices. Explore SQL, NoSQL and web data and build efficient parallel pipelines. Ensure data quality in dataset design. Investigate weaknesses of models in production and implement pragmatic improvements. Utilize, adopt, and fine-tune off-the-shelf models, including LLMs via API and locally hosting LM and other foundation models. Stay current in the field by reading research papers, experimenting with new architectures and LLMs, and sharing findings. Write clean, efficient, modular code with automated tests and documentation. Keep up to date with technology and platforms, justify technical decisions, and communicate them to the organization. Work with downstream teams to productionize work and ensure it makes it into a product release. Communicate insights, behavior, and limitations of models to peers, subject matter experts, and product owners. Present and publish work as appropriate. Qualifications
Required Qualifications: Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, or outstanding achievements in Deep Machine Learning, Computer Science and Software Engineering. At least 5 years of industry experience in Machine/Deep Learning, CS and Software Engineering using the Python ecosystem for ML. Strong understanding of the math and theory behind machine learning and deep learning. Academic publications in peer-reviewed conferences or journals related to Machine Learning (preferably A/A+ rated such as NeurIPS, ICML, ICLR, AAAI, etc.). Machine/Deep Learning development skills with platforms such as AWS SageMaker, Hugging Face, Transformers, PyTorch, PyTorch Lightning, Ray, scikit-learn, Jupyter, Weights & Biases, etc. Understanding of models, training/fine-tuning, and familiarity with industry-standard LM families. Excellent communication and teamwork skills; fluent in written and spoken English. Would be a plus: Software development proficiency; experience with text data to build ML models; experience with other modalities (vision, speech) is a bonus. Computer Science educational background. Familiarity with front-end tools (Gradio, Streamlit, Dash or React/Javascript/Flask) for demos and prototypes. Experience with advanced prompting/agentic systems and fine-tuning or training an LLM using industry platforms. Showcase previous work (website, presentation, open source code). Experience coding for at-scale production, including back-end APIs or libraries. DevOps skills (Docker, AWS EC2/Batch/Lambda). Additional Information
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 is provided in writing at the time of offer and varies by work location and other factors. Total Rewards @ Turnitin Turnitin maintains a Total Rewards package that is competitive within the local job market, including benefits beyond base pay such as time off and health and wellness programs. Our Mission
is to ensure the integrity of global education and meaningfully improve learning outcomes. Our Values
underpin everything we do. Customer Centric
- Educators and learners are at the center of our work. Passion for Learning
- We seek teammates who are constantly learning and growing. Integrity
- The heartbeat of Turnitin in products and interactions. Action & Ownership
- Bias toward action and empowered decision-making. One Team
- Break down silos and collaborate. Global Mindset
- Respect local cultures and think globally to maximize impact. Global Benefits Remote First Culture Health Care Coverage* Education Reimbursement* Competitive Paid Time Off 4 Self-Care Days per year 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
#J-18808-Ljbffr