Teams at Analog Devices

Design and develop cloud-connected intelligent-edge software solutions. Translate system architectures into implementations, build APIs and cloud deployments, package containers for Kubernetes, write tests, implement observability, mentor junior engineers, troubleshoot and integrate features, and collaborate with cross-functional teams to support product development life cycle.

Design, build, and maintain MLOps software systems and ML pipelines; deploy, test, and monitor AI/ML models on cloud-native platforms; implement ETL and data workflows; ensure model performance, security, and scalability; lead technical roadmap, mentor engineers, and evaluate emerging MLOps tools.

Architect and lead AI-hardware co-design solutions from research to validated proofs-of-concept. Quantify compute trade-offs with high-fidelity simulation, optimize algorithms for hardware (memory, dataflow, precision), select compute substrates from MCUs to custom accelerators, mentor engineers, and translate innovation into deployable systems while driving thought leadership in Edge AI.