Senior Backend Engineer – AI, Machine Learning

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AfterNow

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🥽 AR/VR

☁️ SaaS

📚 Education

AR/VR • SaaS • Education

AfterNow is a 3D presentation platform focused on augmented reality (AR) and virtual reality (VR) that helps schools and businesses create immersive, no-code presentations. The company offers a drag-and-drop interface, ready-made 3D assets, and a seamless user experience for use cases such as high-stakes meetings, training, sales, tradeshows, education, and exhibits/museums. AfterNow also positions itself as an Oculus Launch Pad and Microsoft Mixed Reality partner and runs workshops teaching non-technical users how to build AR/VR presentations.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ Benefits

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