Instructure, Inc. - Senior Data Scientist AI/ML Platform Engineer, AI & Analytics

• Strong experience designing and operating production systems on AWS. • Deep understanding of distributed systems, cloud architecture, scalability, reliability, and service design. • Hands-on experience with infrastructure-as-code, CI/CD, Docker, Kubernetes, and production deployment workflows. • Experience building or supporting production ML, AI, data, or high-scale backend systems. • Strong system design skills, including the ability to reason about tradeoffs, failure modes, data flow, service boundaries, and operational complexity. • Ability to communicate clearly across data science, ML engineering, backend engineering, platform engineering, product, and leadership stakeholders. • Experience with SageMaker, Bedrock, ECS, EKS, Lambda, S3, RDS, OpenSearch, Aurora, EventBridge, Step Functions, or related AWS services. • Experience with model serving, batch inference, embedding pipelines, vector databases, RAG systems, or LLM-backed applications. • Experience building ML platform capabilities such as model registries, experiment tracking, evaluation pipelines, inference services, or model monitoring. • Experience supporting both real-time and batch AI/ML workloads. • Experience with workflow orchestration, data pipelines, and production evaluation frameworks. • Experience defining production-readiness standards for AI systems, including evaluation gates, model/version drift, data quality checks, and cost monitoring. • You Might Be a Great Fit If • You enjoy designing systems from first principles and can explain architecture tradeoffs clearly. • You have built infrastructure that other engineers depend on. • You are comfortable operating at both architecture and implementation levels. • You understand that ML systems involve data, models, evaluation, versioning, latency, uncertainty, and operational risk. • You can take an ambiguous AI/ML need and turn it into a practical technical architecture. • You care deeply about scale, reliability, modularity, maintainability, and developer experience. • What Success Looks Like • You understand the AI/ML team’s workflows, infrastructure gaps, and production bottlenecks. • You define reusable architecture patterns that help AI/ML services move from prototype to production. • You establish reliable deployment, monitoring, rollback, and operational standards for AI/ML systems. • You reduce friction for data scientists and applied AI engineers by creating clear production pathways. • You help teams build AI/ML systems that are scalable, secure, observable, and maintainable. • Your work becomes part of the foundation for scaling AI capabilities across Instructure products. • 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. • 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.