Senior Data Scientist, Applied AI

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  Architect, build, and deploy production ML/AI systems that power customer-facing product capabilities

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  Design and operate scalable inference services, APIs, and backend components for model-driven applications

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  Build and improve data, feature, deployment, and orchestration pipelines on AWS across development, staging, and production environments

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  Productionize AI workflows with strong MLOps practices, including CI/CD, versioning, testing, monitoring, rollback, and operational reliability

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  Define and implement evaluation frameworks for model quality, system reliability, latency, and cost, and use those signals to improve production performance

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  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

• 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

• 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

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.