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DOSSIÊ MJ-4437 · ACESSO PARCIAL
Senior Infrastructure Engineer, AI/ML Systems
Instructure · Budapest, Hungary
Esta é 1 de 48.822 vagas encontradas nos últimos 30 dias. Nós comparamos todas com o seu currículo — hoje, esta página nem sabe quem você é.
Grátis, sem cartão. Só o seu currículo.
Encontrada há 2 meses
Se candidatar no escuro custa uma noite.
Saber custa um minuto.
A conta que ninguém faz
Você, sozinho, numa noite
~20
vagas abertas e lidas uma a uma — a maioria descartada no terceiro parágrafo, quando o requisito que você não tem finalmente aparece. Dias assim, toda semana.
O Monster Jobs, enquanto isso
48.822
vagas já lidas e entendidas, prontas para ganhar nota contra o seu currículo no momento em que ele chegar. Você não procura mais vaga — recebe as que merecem a sua atenção.
Recrutador faz triagem de candidato.
Aqui, o recrutador é você — de vagas.
Cada uma chega com nota e motivo. Seu único trabalho é dizer sim ou não.
RELATÓRIO DE COMPATIBILIDADE · GERADO POR VAGA, POR PESSOA
Por que essa nota
Para quem tem conta, este bloco explica a nota em português — escrito sobre o seu histórico, não um texto genérico:
O raciocínio da nota é gerado para cada currículo depois do cadastro gratuito.
A seu favor
O que do seu histórico pesa a favor aqui.
O que falta
O que a vaga pede e seu currículo ainda não mostra.
1 minuto: você envia o currículo, nós escrevemos o resto.
Ninguém caça sozinho. Esta vaga foi encontrada por outra pessoa e entrou no acervo de todo mundo. A caça continua enquanto você lê isto — e a sua parte do acervo (48.822 vagas, comparadas com o seu currículo) só passa a existir quando você entra.
O que você decide sobre cada vaga
Cada vaga vira um caso com histórico: candidatei, entrevista, proposta. Estes botões são os reais — só falta a conta.
Descrição da vaga
At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.
We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:
Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.
This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build.
You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.
What You'll DoBuild and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it
Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
Comfort working through ambiguity and collaborating directly with data scientists and researchers
Experience with ML platform components and data pipeline orchestration at scale
Experience running LLM-based or retrieval-based systems in production
Experience operating specialized data stores, including graph databases
Experience building internal tooling, templates, or reference implementations that other engineers adopted
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.
Why Join UsJoin us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.
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.
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.
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.
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48.822 vagas encontradas nos últimos 30 dias — a sua nota nesta e em todas as outras sai assim que o currículo chega.