Instructure, Inc. - Senior Data Scientist, Applied AI
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Requirements
• 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
Responsibilities
• 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
Benefits
• HUF 1.6M – HUF 2.2M per month • This range reflects our target hiring range, with flexibility based on experience, skills, and market factors. • 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.
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