Python programme állás, munka

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Apply AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• Design, develop and maintain software, tools and applications across the Baseball tracking platform
• Modernise and improve existing software systems
• Develop cross-platform C++ applications and visualisation components
• Participate in code reviews, pair programming and agile ceremonies

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and datasets including comprehensive grading rubrics and high-quality golden datasets
• Optimization of judge prompts for automated scoring alignment

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Providing technical solutions and implementing new software features collaboratively

• Design, build, and ship production retrieval systems
• Own vector store selection and operation
• Build and operate indexing and refresh pipelines
• Implement semantic and hybrid retrieval
• Own retrieval evaluation as a first-class system
• Make and defend the core tradeoffs of the domain

Architect, build, and operate scalable inference services, APIs, and backend components for model-driven and LLM-powered product features...

• Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers
• Define what "mastery" and "progression" mean operationally: constructs, model targets, and evaluation criteria aligned to learning outcomes and product requirements

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines including IaC scanning and policy-as-code