We’re seeking a dedicated Integration Engineer whose primary focus will be integrating machine learning models into our flagship product. You’ll bridge the gap between data science and production software—implementing, deploying, and maintaining ML-powered features while contributing to back-end services and React-based front-end components. Your work will enable seamless, scalable AI capabilities for end users.

Not sure if you have enough experience to meet the challenge, but still willing to learn and join our team? Send us your application and we will be happy to talk about the possibilities. Think big!

Why Join OneRail Poland?

• Innovation at its Core: Work on industry-leading technology that is shaping the future of logistics.
• Career Growth: Opportunities for professional development and career advancement.
• Collaborative Culture: Join a team of talented engineers and industry experts.
• Exciting Challenges: Solve complex problems and contribute to impactful projects.
• Flexibility: We offer a flexible hybrid work style and flexible employment types to suit your needs, ensuring a work-life balance that works for you.
• Competitive Compensation: Attractive salary and benefits package.

Office location: Kraków, Poland
Work Style: Hybrid (2-3 days from the office / week preferred).

Salary level: 20 000 – 27 000 PLN/ month

Take the next step in your career and become a part of OneRail’s exciting journey!

Daily Tasks:

• Work with ML pipeline engineers to deploy and maintain ML models (e.g., PyTorch, scikit-learn) as robust service endpoints.
• Collaborate with data scientists and product to productionize prototypes, and extend the product to enable ML and AI features.
• Define and evolve RESTful APIs with OpenAPI/Swagger—ensuring they support low-latency, high-throughput ML inference.
• Version, document, and maintain API contracts for internal and external consumers.
• Build microservices (Python—FastAPI/Flask—or Node.js) that encapsulate ML logic, data pre/post-processing, and business rules.
• Optimize service performance, scalability, and reliability (caching, async processing, batching).
• Implement and modify React components and pages to expose ML-driven functionality
• Ensure seamless data flow from back end to front end, handling streaming or polling as needed.
• Containerize ML services (Docker) and orchestrate deployments
• Work closely with cross-functional teams (data science, product, QA) to translate ML requirements into production features.
• Champion code quality, API versioning strategies, and thorough documentation.