Principal ML Solutions Architect

ARM

Austin, Texas, United States

Austin, Texas, United States

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About

This role is part of the rapidly growing Arm Infrastructure Line of Business where we enable deployment of Arm Neoverse cores in Cloud, Edge, 5G and Networking segments! To enable successful adoption, we need to understand how customers in these segments deploy Machine-Learning and identify what workloads and software are needed by the development community to run their applications on Arm platforms. ML Solutions Architect will define requirements and strategy to drive growth and success of Arm for key ML applications. Responsibilities: Architect ML solutions that bring together Arm’s products, technologies, software, and ecosystem and provide best-in-class performance, power efficiency and scalability. Work with multi-functional teams including hardware engineers, software developers, performance engineers, and researchers to align ML strategies with system design goals. Engage with end customers such as Hyperscalers, OEMs, ML system and software companies to understand ML use-cases, requirements, and opportunities for Arm. Keep pace with the latest advancements in ML space, drive competitive analysis and find innovative solutions to prepare Arm for success. Support Product Managers on defining ML requirements for software and next-gen hardware. Promote Arm ML solutions with Arm partners and wider industry, demonstrating both maturity of vision and technical leadership. Represent Arm’s interests at key ML industry forums and technology working groups with goal of enabling widespread adoption of Arm solutions. Required Skills and Experience :
MS or PhD in Electrical Engineering or Computer Engineering (other degrees will be considered with relevant work experience) 10+ years as a systems/solutions architect with a background in ML and other Cloud workloads and applications. Deep understanding of ML system architecture including ML models (BERT, LLMs, DLRM), frameworks (TensorFlow, PyTorch), runtime engines and their mapping to key hardware primitives (SIMD engines, system-architecture). Experience helping customers deploy ML in various use-cases including NLP, Vision, Data-analytics – covering both emerging applications like GenAI as well as Traditional ML applications. Good communication and collaboration skills, ability to build technical consensus across multiple teams and bring clarity to poorly defined and complex problems.
“Nice To Have” Skills and Experience :
Knowledge of Cloud application architecture, components that integrate with ML – e.g. Databases, web, runtime languages, orchestration, storage etc. Understanding of systems and software architecture and their impact on hardware designs and vice-verse. Knowledge of Arm eco-system of software and hardware partners. Ability to generate consistent, complete, and concise written specifications. Experience driving industry standards and presenting at various industry technical forums and events.
In Return: Arm is poised to lead the next generation of innovation, adoption and growth in the Machine Learning space ! This is an outstanding opportunity to influence the direction that the industry is taking and learn emerging trends in this space. LI-LB1 Accommodations at Arm At Arm, we want our people to Do Great Things. If you need support or an accommodation to Be Your Brilliant Self during the recruitment process, please email accommodations@arm.com. To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process. Hybrid Working at Arm Arm’s hybrid approach to working is centred around flexibility, where we split our time between the office and other locations to get our work done. Within that framework, we empower groups and teams to determine their own particular hybrid working pattern, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you. #J-18808-Ljbffr

Austin, Texas, United States

Languages

English

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