Teams at Qutwo

Productize machine learning pipelines for deep neural network compression and build secure, observable SaaS products. Responsibilities span ML training and inference workflows, backend services, frontend development, cloud infrastructure, containers, Kubernetes, CI/CD, observability, and security. The role owns architecture, deployment, operations, cost efficiency, and technical trade-offs involving model size, latency, memory, and accuracy. Candidates need broad production engineering experience, practical PyTorch or TensorFlow expertise, security awareness, and strong cross-functional communication skills.

Develop, implement, and benchmark classical and quantum optimization solutions for enterprise problems. Translate business problems into mathematical models, design QUBO/quantum approaches, use major quantum frameworks, and communicate results to customers and interdisciplinary teams.

Lead and coordinate multi-quarter enterprise design partnerships, translating strategic customer ambitions into executable technical scope, driving deployments, customer success, expansion, and codifying playbooks across BD, R&D, product, and client teams.