Deloitte AI Systems Architect - Senior Manager in Charlotte, North Carolina
Deloitte is hiring to scale up and the next generation of its AI infrastructure. Deloitte recently launched the Deloitte Center of AI Computing, a first-of-its-kind center designed to accelerate the development of innovative AI solutions at Deloitte. This position will help harness the value of NVIDIA DGX and industry-leading software and GPU technologies used in AI workloads and high performance computing.
This is an opportunity to join the team and be fully hands-on to help drive technical strategy, cluster management, AI workload design, and make such resources available to a broad base of engineering and consulting groups. Work within the Deloitte Center for AI Computing to deliver and optimize the accelerated platform that allows Deloitte to co-innovate with clients and expedite the development of new AI applications. The candidate will help define solution integration practices and represent emerging technology needs inside the company with emphasis on the latest GPU technologies for high performance computing.
Work you'll do
Work within the Deloitte data center group to design and optimize architecture and technical specifications for the NVIDIA hardware-enabled data center
Collaborate with internal stakeholders to understand future NVIDIA deployments and data center requirements to support their project exigencies and improve DGX mini-pod efficiency
Utilize your capabilities in DevOps, DataOps, and IT architecture design to streamline infrastructure processes and optimize scheduling and performance
Understand business priorities and future goals and translate to optimized infrastructure tools and improved service delivery
Coordinate with data science and business teams to identify future AI needs and requirements
Manage system operations for data processing and AI workloads
Provide technical architecture leadership with the responsibility to ensure the efficient use of resources, the selection of appropriate technology, and the use of appropriate design methodologies
Provide leadership and prioritization for business/product stakeholders in understanding requirements and translating them to engineering requirements
Analyze current data designs to optimize and provide structural improvements to handle the growth of workloads
Support and enhance data architecture, data instrumentation, define database schemas, create ETL pipelining as required to internal customer needs
Work in DataOps/DevOps/DevSecOps to bring up new data systems and supporting existing orchestration and data services
Influence domain-driven design and architecture principles of data lineage, data security, data privacy, data uptime, and reliability
Define and grow HPC/AI infrastructure and best practices
Set-up alerting, reports, and dashboard for monitoring overall system health
Provide reports and updates on usage, maintenance, and debugging in an agile environment
Bachelors in Computer Science (CS), Computer Engineering (CSEE), or related STEM field or equivalent experience
Expert with GPU computing (CUDA, OpenCL) and HPC system software stack
Expert programming skills in Linux Shell/CLI, Python, Powershell (bash/(t)csh, grep/ sed/cut, vim/nano, nvidia-smi etc)
Strong knowledge and understanding of CI/CD processes and deployment tools, including Kubernetes, Jenkins, Docker
Experience with resource management systems and job scheduling, including parallel programming experience
Experience developing large-scale data management systems (PB+) and serving dozens of users/data scientists
Experience with provisioning and configuration management tools; Puppet, Ansible, Chef, Terraform, etc
Excellent critical thinking, verbal communication, and problem-solving skills
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
MS/Ph.D. in Computer Science (CS), Computer Engineering (CSEE), Electrical Engineering (EE), or related/relevant STEM degree.
Experience in a private cloud, hybrid cloud, and HPC in cloud managed services
Experience with enabling modern deep learning software architectures and frameworks including Tensorflow, PyTorch or other frameworks
Ability to engage executive audiences to lead AI engineering and data science engagements
AWS/Azure Certifications a plus
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