🚀 Project Description

We are building an MVP for a digital planning platform.

The platform will allow doctors to upload 3D dental scans, run ML-powered processing, and use the results inside a planning workflow

From the engineering side, this role is focused on Backend + DevOps / MLOps, with strong ownership over the technical foundation of the product.

The main goal is to create a reliable environment for deploying and serving ML models, building processing pipelines, exposing APIs, and using AI Tools for maximum productivity.

✅ You are:

• Have practical experience from commercial projects, pet projects, hackathons, or open-source contributions
• Confident with Python or Java, with readiness to work close to ML workloads and model-serving pipelines
• Comfortable building backend services and REST APIs
• Understand system design, asynchronous processing, and service integration
• Have experience with Docker and deploying services in cloud environments
• Understand how to build and maintain CI/CD pipelines
• Have hands-on experience with AWS or similar cloud platforms
• Are comfortable working with PostgreSQL
• Can design and implement backend components that interact with ML models
• Understand logging, monitoring, environment setup, and deployment workflows
  

➕ Will be a plus:

• Experience with MLOps or model-serving infrastructure
• Experience deploying ML models for inference on CPU
• Familiarity with FastAPI, Spring Boot, or similar backend frameworks
• Experience with AWS services
• Understanding of job queues, background workers, and long-running processing workflows
• Experience with 3D, computer vision, or scan-processing products
• Familiarity with infrastructure-as-code tools such as Terraform
• Comfortable working with AI platforms and developer tools such as Cursor, Claude Code, or Codex
  

♟️ What We Expect from You:

• Use modern AI tools, frameworks, and approaches to work faster and more effectively
• Make practical decisions that help us launch faster without unnecessary overengineering
• Proactively identify bottlenecks, propose solutions, and help shape technical decisions
• Be comfortable working in an evolving product with changing priorities and early-stage ambiguity
  

🔑 Responsibilities:

• Implement and enhance backend services for the MVP
• Create the initial cloud environment for development, testing, and production
• Set up and maintain deployment pipelines
• Deploy and serve ML models on CPU-based infrastructure
• Build and support processing pipelines for model execution and result delivery
• Work closely with the ML engineer to integrate segmentation, alignment, and other model outputs into the platform
• Configure logging, monitoring, and basic operational observability
• Ensure the system is reliable, maintainable, and easy to extend
• Utilize AI to review pull requests and contribute to engineering best practices
  

🍩 What we offer:

• Opportunity to work on an innovative product in the medical-tech domain
• High ownership and direct impact on product architecture
• Flexible work hours within the European time zone
• A fast-moving environment where strong engineers can influence product and technical decisions
• Paid 200$+ AI assistants and modern engineering tooling
• Professional development support, latest courses and certifications
• 20 business days of vacation
• 5 sick leave days
• National holidays covered
  

🗣 Recruitment process:

✔️ Culture Fit Interview → ☑️ Technical Task → ✅ Follow-Up Interview → 🏁 Final Technical Interview