Teams at Quantiphi

Build and deploy end-to-end machine learning solutions, with a strong focus on computer vision, image processing, model development, feature engineering, cloud platforms, MLOps, monitoring, and CI/CD. Collaborate with stakeholders and IT teams across multiple engagements, follow Agile methodologies, ensure project delivery quality, and contribute to research and development.

Design, architect, and implement highly available video streaming and inference platforms. Build and maintain Kubernetes and Docker infrastructure, CI/CD pipelines, monitoring, alerting, deployment strategies, and distributed systems. Develop production-grade Python backend services using Flask and Gunicorn, integrate databases and streaming pipelines such as Redis and Kafka, and troubleshoot Linux-based container environments. Collaborate with machine learning research and production DevOps/MLOps teams.

Own backend and infrastructure architecture while developing Python and PHP services, APIs, authentication integrations, and database solutions. Design and maintain GCP infrastructure, Docker environments, CI/CD pipelines, monitoring, security, backups, and disaster recovery. Lead technical decisions, cloud optimization, incident response, documentation, and collaboration with frontend teams on headless CMS and SaaS deployments. Advise stakeholders on technical approaches, costs, risks, and estimates while mentoring engineers and supporting client-facing initiatives.