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 Advanced Development team builds AI-native capabilities, reusable AI systems, and shared infrastructure that power multiple products and workflows across the platform.
We are looking for a Senior Data Scientist to help build, ship, and scale production AI systems from the ground up. This is an engineering-forward ML/AI systems role, intended for candidates who are comfortable moving from prototype to production and can own critical parts of the ML/AI systems lifecycle, including pipelines, model integration, inference services, deployment, monitoring, and operational reliability.
You will work closely with product, engineering, and research partners to turn advanced AI ideas into reliable product capabilities used at scale.
Important note on scope: This role is not primarily focused on BI/reporting or experimentation analytics. We are looking for someone with strong experience building and operating production ML/AI systems.
What You’ll Do
Architect, build, and deploy production ML/AI systems that power customer-facing product capabilities
Design and operate scalable inference services, APIs, and backend components for model-driven applications
Build and improve data, feature, deployment, and orchestration pipelines on AWS across development, staging, and production environments
Productionize AI workflows with strong MLOps practices, including CI/CD, versioning, testing, monitoring, rollback, and operational reliability
Define and implement evaluation frameworks for model quality, system reliability, latency, and cost, and use those signals to improve production performance
Partner with product, research, and engineering teams to turn prototypes into robust, scalable services, while driving strong engineering standards in code quality, documentation, observability, and incident readiness
What You’ll Need
6+ years of experience in software engineering, machine learning engineering, applied AI engineering, or a closely related role with production ownership
Demonstrated experience taking ML/AI systems from prototype to production in live environments
Strong experience with deployment pipelines, CI/CD, orchestration, and operating production services on AWS
Experience building and operating APIs/services (Python preferred), working with containers, and debugging reliability/performance issues
Working knowledge of modern AI application patterns (for example, embeddings, retrieval, semantic search, or RAG) and the engineering constraints involved in running them in production
Strong communication skills and the ability to work through ambiguity across engineering, product, and research teams
Onsite 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.
It Would Be a Bonus If You Had
Experience building AI-native product features (not just internal analytics models)
Experience with vector databases, retrieval infrastructure, or semantic indexing pipelines
Experience with graph databases or graph-based reasoning systems
Experience with observability and evaluation for LLM or retrieval systems (quality metrics, drift, failure analysis)
Experience creating internal engineering standards, templates, or reference implementations adopted by multiple teams
Experience in education technology, learning systems, or knowledge/skills modeling
Experience mentoring engineers in a high-growth or platform-building environment
Growth & Impact - In This Role, You’ll Be Expected To
Influence architecture and engineering standards for AI systems
Shape reusable infrastructure and platform patterns
Mentor a growing team of AI/ML engineers
Turn advanced AI research into production value for educators and learners at scale
Why Join Us
Join 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 Advanced Development team, a research-driven group tackling education’s biggest challenges with cutting-edge technology. Our projects have included making sense of unstructured feedback, applying large language models to save teachers’ time and improve student experiences, classifying partner networks for smarter recommendations, and detecting fraud to protect resources for real learners.
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 support
Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
The technology and tools you need to do your best work
Motivosity employee recognition program
A culture rooted in inclusivity, support, and meaningful connection
We 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.
Instructure Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Instructure and has not been reviewed or approved by Instructure.
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Fair & Transparent Compensation — Pay is considered market-competitive for many engineering, product, and quota-carrying roles, especially when factoring base, variable, and equity. In these tracks, total rewards are often characterized as fair-to-strong for the role and location.
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Healthcare Strength — Health coverage is described as comprehensive, including medical, dental, vision, mental-health support, and HSA/FSA options. Employer contributions are often portrayed as strong, and core medical benefits receive consistently positive marks.
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Leave & Time Off Breadth — Time off offerings include flexible or “unlimited” PTO, paid holidays, and paid sick time, paired with widespread remote/hybrid flexibility. This breadth of time off and work flexibility is often viewed as a meaningful perk that enhances overall value.
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What We Do
Instructure is helping people grow from the first day of school to the last day of work. More than 30 million people use its Canvas and Bridge platforms for learning management and employee development.
