Machine Learning Engineer

The Integration Engineer will integrate machine learning models into a delivery orchestration product, bridging data science prototypes and production software. The role includes building and maintaining ML-powered back-end services and React-based front-end functionality to provide scalable AI capabilities.

Key Responsibilities

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

Requirements

• 3+ years of professional full-stack development, with a track record of integrating ML into production systems.
• Hands-on experience serving models in production, including model serialization, serving frameworks, and inference optimization.
• Strong TypeScript and Python proficiency.
• Experience with microservices architecture, message brokers such as Kafka, and asynchronous frameworks.
• Solid React knowledge, including hooks, context, and state management.
• Deep understanding of REST principles, OpenAPI/Swagger, API versioning, and backward compatibility.
• Docker and orchestration experience.
• Experience with CI/CD pipelines (GitHub Actions, Jenkins, or GitLab CI) and automated unit, integration, and end-to-end testing.
• Advanced written and spoken English (B2+).

Benefits

• Professional development and career advancement opportunities.
• Collaborative work with engineers and industry experts.
• Flexible hybrid work style and flexible employment types.
• Competitive salary and benefits package.
• Hybrid work preferred: 2–3 days from the office per week.
• Salary: 20,000–27,000 PLN per month.