Senior Machine Learning Engineer (Python+Kubernetes)

Synopsys' Generative AI Center of Excellence defines the technology strategy to advance applications of Generative AI across the company. The Gen AI COE pioneers the core technologies - platforms, processes, data, and foundation models - to enable generative AI solutions, and partners with business groups and corporate functions to advance AI-focused roadmaps. We are looking for an experienced, passionate, and self-driven individual who possesses both a broad technical strategy and the ability to tackle architectural and modernization challenges. As an Ideal candidate will help build enterprise Machine Learning platform. They will work with a team of enthusiastic and dynamic ML engineers and Data scientists in building a platform to help Synopsys R&D teams to experiment, train models and build Gen AI & ML products. You will be responsible for:Building ML Platform to orchestrate enterprise-wide Data pipelines, ML training, and inferencing servers.Develop "ML App Store" eco system to enable R&D teams build Gen AI and ML products in CloudOrchestrate GPU Scheduling from within Kubernetes eco-system (e.g. Nvidia GPU Operator, MIG, and so on)Create reliable and cost-effective Hybrid cloud architecture using cutting edge technologies (E.g. Kubernetes Cluster Federation, Azure Arc and so on)Required QualificationsBS/MS/PhD in Computer Science/Software Engineering / Mathematics or an equivalent degree8+ years of total experience building systems software, enterprise software applications, ML applications and microservicesExpertise and/or experience in following programming languages : Python, and GoDesign complex distributed systems (High-level and low-level systems design)Building SDKs to enterprise software systemsIn-Depth Kubernetes knowledge: Be able to deploy Kubernetes on-prem, and working experience with managed Kubernetes services (AKS/EKS/GKE)Strong systems knowledge in Linux Kernel, CGroups, namespaces, and DockerExpertise with at least one cloud provider (AWS/GCP/Azure)Ability to solve complex problems using efficient algorithmsExperience with using RDBMS (PostgreSQL preferred) for storing and queuing large sets of dataNice to have:Prior experience with AI/ML workflows and tools (PyTorch, ML Flow, AirFlow, …)Experience prototyping, experimenting, and testing with large datasets, and analytic data flows in productionStrong fundamentals in Statistics, Machine Learning, and/or Deep Learning PRB