Instructure, Inc. - Senior Data Scientist, AI Platform
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• 6+ years of experience in software engineering, machine learning engineering, or applied AI engineering, with clear ownership of systems in production • Demonstrated experience taking ML and LLM systems from prototype to production and operating them in live environments. This is a hard requirement; we are not looking for a strong infrastructure engineer who has not worked with AI systems • Strong experience building and operating APIs and services (Python preferred), working with containers, and debugging reliability and performance issues in production • Strong MLOps skills: deployment and orchestration pipelines, model and artifact versioning, monitoring, and rollback for ML and LLM workloads • Working knowledge of modern AI patterns (embeddings, retrieval, semantic search, RAG) and their production constraints • It Would Be a Bonus If You Had • 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, including quality metrics, drift, and failure analysis • A track record of internal engineering standards, templates, or reference implementations adopted by multiple teams • Experience mentoring engineers in a high-growth or platform-building environment • Experience in edtech, learning systems, or knowledge and skills modeling • Growth & Impact - In This Role, You'll Be Expected To • In this role, you will own the ML systems and MLOps foundation that every AI capability on the team depends on. You will shape the architecture, standards, and reference patterns that let modeling and retrieval specialists ship their work reliably, and you will be the person who makes production AI at Instructure dependable, observable, and repeatable.
Responsibilities
• Architect, build, and operate scalable inference services, APIs, and backend components for model-driven and LLM-powered product features • Productionize AI and ML workflows with strong MLOps practices: model versioning, testing, deployment pipelines, monitoring, rollback, and operational reliability • Define and implement evaluation frameworks for model quality, system reliability, latency, and cost, and make these a standard part of how models ship • Build reusable platform patterns, service templates, and reference implementations that multiple teams and products can adopt • Set and uphold engineering standards across the AI team: code quality, documentation, observability, and incident readiness, and mentor team members in production ML practices • Partner with our infrastructure owner on the underlying cloud, cluster, and CI substrate, and with product, engineering, and research partners to move AI capabilities into production
Benefits
• 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. 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 enviro • 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.
No credit card. Takes 10 seconds.