About The Role

At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.We're looking for a Senior Machine Learning Engineer to build and own the learner models behind our mastery and progression capabilities. You'll design the models, build the pipelines that train and score them, and own their quality once they're running in <production.You>'ll partner with our learning scientists on what these models should measure, and with our infrastructure team on deployment and operations.What You'll DoDesign and build learner models, including knowledge tracing and longitudinal approaches, that power mastery and progression features surfaced to learners and educatorsShape the data foundation for learner modeling: define which signals matter, and build the datasets your models depend onTranslate mastery and progression definitions into model targets and evaluation criteria, working with learning scientists and product partnersBuild estimation and scoring approaches that hold up on sparse, noisy, and evolving behavioral dataOwn your models in production: training and scoring pipelines, testing, versioning, and monitoring quality once they're liveExplain model behavior, assumptions, and limitations clearly to product, engineering, and learning partnersWhat You'll NeedSix or more years in applied machine learning, machine learning engineering, or applied research, with ownership of models shipped into real productsDepth in at least one of: sequence modeling, latent-variable or probabilistic modeling, temporal modeling, Bayesian methods, or calibration of model outputs, applied to data that changes over timeStrong Python and production engineering skills: you write the pipelines that train and score your models, and you've shipped models that run on a schedule and serve predictions to real usersStrong evaluation instincts around calibration, uncertainty, stability, fairness, interpretability, and validation strategyIt Would Be a Bonus If You HadExperience with recommender systems, user-state modeling, or personalization at scaleExperience with knowledge tracing, psychometrics, educational measurement, or adaptive learning systemsExperience combining structured knowledge representations, such as skills, standards, or concept graphs, with learner modelsExperience designing experiments or observational validation strategies to test whether a model reflects realityOnsite Collaboration Requirement: This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.Why Join UsJoin us and help shape the future of education by turning cutting-edge AI into reliable product <capabilities.At> Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.Get in on all the awesome at Instructure!We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.Comprehensive wellness programs and mental health supportLearning and development resources, including professional development tools and tuition reimbursement, to support your growthThe technology and tools you need to do your best work Motivosity employee recognition programA culture rooted in inclusivity, support, and meaningful connectionWe believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.Any attempt to misrepresent personal or professional information will result in disqualification.