Jobs at Q Innovations

Design and deliver a production-grade API platform, integration frameworks, identity/profile systems, and high-reliability event streaming infrastructure. Implement authentication/authorization (OAuth2/OIDC), secure multi-tenant access, and enterprise integration layers so external services and institutional customers can embed platform capabilities reliably.

Lead design of a consumer-facing platform: define information architecture, build scalable design systems, design AI-powered and discovery/search interfaces, craft transactional flows and motion principles, and ensure accessibility and production-ready components.

Design and build consumer-facing search, social, and transactional interfaces and the full stack beneath them. Own frontend performance, real-time features, API contracts, backend services, state management, and production-grade error handling to deliver polished user experiences from design to production.

Design and build payment orchestration, transactional and reconciliation systems, digital wallets, billing/accounting, and robust failure handling. Integrate third-party commerce APIs, ensure auditability and replayable event logs, and apply PCI DSS and idempotent engineering practices.

Design and build production-grade large-scale graph systems and analytics pipelines. Develop GNN architectures and serving pipelines for low-latency updates, apply graph techniques to organizational data, and ensure privacy-preserving infrastructure while operationalizing research at production scale.

Design and build production-grade personalization and recommendation systems using sequential modeling and online learning. Implement feature engineering pipelines for high-volume event streams, real-time content delivery, exploration-exploitation frameworks, feedback/learning infrastructure, and evaluation methods to ensure genuine personalization while avoiding overfitting.

Design and build production-grade agentic AI systems: multi-agent pipelines, LLM orchestration, tool-use and function-calling infrastructure, task decomposition, reliability and recovery layers, and evaluation infrastructure that connects AI reasoning to real-world APIs and measures multi-step execution reliability.

Design and build production-grade semantic search and retrieval systems: query understanding, dense retrieval (bi-/cross-encoders), re-ranking, RAG pipelines, fine-tuning LLMs, and precision evaluation across multilingual query distributions.

Lead design and build end-to-end ML architectures and pipelines for real-time personalization and relevance. Develop large-scale training, low-latency serving, experimentation and evaluation platforms, and establish ML engineering standards for production-grade reliability, monitoring, and incident response.

Design and operate cloud infrastructure and Kubernetes-based orchestration for large-scale consumer ML products. Build model-serving, GPU management, CI/CD, data architecture with access controls, and full observability for production reliability, performance, and cost efficiency.