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 AI Platform for Synopsys to orchestrate enterprise-wide Data pipelines, ML training, and inferencing servers.
  • Develop "AI App Store" eco system to enable R&D teams to host Gen AI applications in Cloud
  • Develop capabilities to ship Clou Native (Containerized) AI applications/AI systems to on-premises customers
  • Orchestrate 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 Qualifications

  • BS/MS/PhD in Computer Science/Software Engineering or an equivalent degree
  • 10+ years of total experience building systems software, enterprise software applications, ML applications and microservices
  • Expertise and/or experience in following  programming languages :  Python, and Go
  • Design complex distributed systems (High-level and low-level systems design)
  • In-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 Docker
  • Experience with at least one cloud provider (AWS/GCP/Azure)
  • Ability to solve complex problems using efficient algorithms
  • Experience with using RDBMS (PostgreSQL preferred) for storing and queuing large sets of data

Nice 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 production
  • Strong fundamentals in Statistics, Machine Learning, and/or Deep Learning
Is a Remote Job?
No

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