- Palo Alto, CA
The VMware Engineering Services team ensures our internal and external customers enjoy a high-quality experience across the entire product portfolio. Our goal is to provide compelling, innovative, scalable, and seamless engineering services, which will protect VMware's brand reputation by continually improving customer satisfaction. We bring together key R&D functions such as build, performance, security, release management (and more), which frees up R&D business units to focus on product innovation. Our priorities include investing in R&D talent, sharing best practices, and driving scale and agility in VMware products.
Come join the VMware's Central Performance Engineering team. We are a diverse organization of creative thinkers who use conventional as well as AI approaches to solving cross product performance problems, from platform, storage, networking, management products to SaaS and hybrid cloud. We drive efficiency, improve the bottom line and have fun while doing it. Our products and services drive a measurable impact on the business, we do the things that matter. Our team defines performance standards and is closely involved in products design and architecture to ensure they are fundamentally built for high performance and scalability. The team plays a critical role in taking products to market by generating performance highlights and educating customers on sizing and performance best practices. Research is ingrained in our DNA. We invent new technologies that enable our products to scale to next generation hardware and applications. We advance through research, development and domain expertise the future of AI within the company.
Make a difference in your career - be part of something bigger than all of us - Join the VMware Performance and Analytics family.
Job Role & Responsibility
VMware is looking for a Sr. MTS ML Engineer interested in joining the Performance Team to work on VMware's pioneering, machine assisted self-driven software defined data center project. The candidate would need to use their experience to drive explaining, debugging, and improving reinforcement learning models that drive performance considerations at the hardware, hypervisor, guest OS layers into an overall understanding of why self-driven systems perform as they do, and then to communicate what is learned to the appropriate stakeholders. The position involves working with other performance engineers as well as developers and data scientists to improve core products, developing best practices, authoring blogs and white papers, and presenting internally, at conferences, and directly to partners and customers. You'll be part of a bright engineering team that has an open communication, empowerment, innovation, teamwork and customer success culture.
- A PhD or master's in computer science or related field
- 5+ Years of relevant industry experience
- Solid understanding of and hands-on experience in large distributed systems
- Understanding of ML model algorithms and architecture
- Proficiency in Python
- Working knowledge of Linux/Unix
- Capable of architecting/understanding complex software solutions
- Excellent analytical and debugging skills
- Excellent verbal and written communication skills and team player
- Experience with Tensorforce or other reinforcement learning library
- Experience with ML model training
- Experience with ML model explanation
- Experience in getting AI/ML working in real systems
- Basic hypervisor system administration skills
- Experience in system software development, testing and performance engineering
- Experience or interest in building software with continuous integration and deployment
- C, C++ programming
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