Senior Data Scientist, AI Platform

Instructure

Senior Data Scientist focusing on AI Platform and optimizing machine learning lifecycle. Collaborating with teams to deliver scalable AI product capabilities.

Posted 6/3/2026full-timeBudapest • 🇭🇺 HungarySeniorWebsite

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learning engineeringapplied AI engineeringMLOpsmodel versioningdeployment pipelinesmonitoringAPIsPythoncontainersdebugging

Soft Skills

mentoringengineering standardscode qualitydocumentationobservabilityincident readinesscollaboration