Senior Backend Engineer – AI, Machine Learning

Vaga não está no LinkedIn

🕒 Julho 27

🇩🇪 Alemanha – Remoto

💵 €3.000 - €4.000 / mês

⏳ Contrato/Temporário

🟠 Sênior

🔙 Engenheiro Backend

👻 Score fantasma 8%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

Candidatar-se

Encontrar Vagas Remotas Similares

Configurar Alerta de Email para Novas Vagas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

AfterNow

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2016

🥽 AR/VR

☁️ SaaS

📚 Educação

AR/VR • SaaS • Education

AfterNow é uma plataforma de apresentações 3D focada em realidade aumentada (AR) e realidade virtual (VR) que ajuda escolas e empresas a criar apresentações imersivas, sem a necessidade de programação. A empresa oferece uma interface de arrastar e soltar, ativos 3D prontos para uso e uma experiência de usuário perfeita para casos de utilização como reuniões de alta importância, treinamentos, vendas, feiras, educação e exposições/museus. A AfterNow também se posiciona como parceira do Oculus Launch Pad e da Microsoft Mixed Reality e realiza workshops ensinando usuários não técnicos a construir apresentações em AR/VR.

Descrição

• Design, implement, and deploy machine learning features in production environments • Build reliable data pipelines for processing, transforming, and preparing data for ML models, analytics, and intelligent product features • Create internal (gRPC) and external (REST) APIs that allow AI/ML services to be consumed by other applications and systems • Support experimentation, validation, monitoring, and continuous improvement of ML models and AI-driven features • Ensure that ML-powered features are reliable, performant, maintainable, and built to scale • Work closely with product managers, backend engineers, frontend engineers, QA, and design teams to define, refine, and deliver intelligent product experiences • Own AI and ML capabilities from technical discovery and prototyping through production deployment, monitoring, maintenance, and iteration • Work with DevOps and backend teams to deploy, monitor, and scale ML-powered services in AWS cloud environments • Use coding agents and AI development tools to improve development speed, testing, documentation, and code quality, while remaining accountable for architecture, security, reliability, and production outcomes • Develop and maintain dedicated AI/ML services, primarily using Python and modern backend engineering practices • Integrate, serve, and maintain ML models within scalable backend systems and microservices architectures • Define evaluation criteria, test datasets, monitoring, tracing, and quality metrics for AI-powered features • Identify failure modes and implement appropriate safeguards and fallback behaviour

🎯 Requisitos

• 5+ years of backend development experience with Python & preferably Java Spring Boot • Strong hands-on experience with Python and common ML/data libraries and frameworks • Experience building and deploying production-grade machine learning features, not only experiments or notebooks • Solid understanding of data pipelines, model serving, APIs, and backend system integration • Experience with MLOps tools and workflows, cloud infrastructure, preferably AWS • Familiarity with microservices architecture and modern backend engineering practices in Java • Understanding of ML lifecycle concepts such as training, evaluation, deployment, monitoring, and iteration • Experience with databases, data processing, and structured/unstructured data • Familiarity with NLP, RAG, LLMs, recommendation systems, prediction models, vector databases, embeddings, agentic AI systems, tool calling, workflow orchestration, or other applied AI/ML domains is a strong plus • Ability to translate complex data and ML concepts into practical, usable product features • Strong problem-solving skills and a pragmatic engineering mindset • Hands-on experience using AI coding tools or agents as part of a professional software development workflow • Experience evaluating AI or ML systems using automated tests, offline evaluations, production metrics, and human feedback • Clear communication skills and the ability to collaborate with technical and non-technical stakeholders • Languages: Fluent in English to seamlessly integrate with our international team and clientele. Since the product is focused on the Latin American market, being Spanish-speaking is an advantage.

🏖️ Benefícios

• Flexibility • Remote work & Tooling • Culture • Autonomy and responsibility