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Hpc Systems Engineer Jobs in Michigan (NOW HIRING)

Lead Cloud HPC- AI Infrastructure Architect(S2S) As a Lead Cloud Integrated Infra Engineer on the ... Linux system administration in production environments * 3+ years designing or operating ...

HPC architecture & technical standards (20%) * Define target-state architecture and standards ... Bachelor's degree in computer science, Engineering, Information Systems, or equivalent practical ...

Water Treatment Technician

Ludington, MI · On-site

$14.42 - $28.85/hr

Escalate issues beyond field repair capability to engineering or OEM support with detailed ... HPC-Industrial offers an exceptional three-pronged safety system, innovative career development ...

HPC-Industrial offers an exceptional three-pronged safety system, innovative career development ... Escalate issues beyond field repair capability to engineering or OEM support with detailed ...

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Hpc Systems Engineer information

What is an HPC systems engineer?

HPC Systems Engineers are professionals who design, deploy, manage, and optimize high-performance computing (HPC) systems. These systems are used for complex computational tasks in fields such as scientific research, engineering, and data analytics. HPC Systems Engineers ensure that computing clusters, storage solutions, and networking components run efficiently, securely, and reliably. They also support users, troubleshoot issues, and often work with specialized software, hardware, and parallel processing technologies.

What are the key skills and qualifications needed to thrive as an HPC systems engineer?

To thrive as an HPC Systems Engineer, you need a solid background in computer science, Linux/Unix system administration, and parallel computing concepts, often supported by a relevant degree. Experience with HPC cluster management tools, workload schedulers (like Slurm or PBS), and programming languages such as Python or C/C++ is typically required. Strong problem-solving skills, attention to detail, and the ability to communicate technical concepts clearly are essential soft skills. These qualifications ensure efficient deployment, maintenance, and optimization of high-performance computing infrastructure critical for research and enterprise workloads.

What are some common challenges an HPC systems engineer faces when supporting large-scale computing clusters?

HPC Systems Engineers often encounter challenges such as managing the complexity of cluster architectures, ensuring optimal performance, and troubleshooting hardware or software issues in high-demand environments. They must also coordinate downtime for maintenance without disrupting critical computations and stay updated on rapidly evolving HPC technologies. Strong collaboration with researchers, IT staff, and vendors is essential to address user needs and implement effective solutions.

What is the difference between Hpc Systems Engineer vs Hpc Network Engineer?

AspectHpc Systems EngineerHpc Network Engineer
CredentialsTypically requires a degree in computer science, engineering, or related field; certifications like Cisco CCNA or Linux certifications are commonSimilar credentials; often holds networking certifications such as Cisco CCNP or CompTIA Network+
Work EnvironmentWorks on high-performance computing systems, hardware, and software integration in research or enterprise data centersFocuses on designing, implementing, and maintaining HPC network infrastructure within data centers or research facilities
Industry UsageUsed in scientific research, academia, and enterprise sectors with HPC needsCommon in data centers, research institutions, and organizations requiring advanced network performance

Hpc Systems Engineers and Hpc Network Engineers share overlapping skills in hardware, software, and certifications. However, Hpc Systems Engineers focus on overall system setup and management, while Hpc Network Engineers specialize in network infrastructure. Both roles are vital in supporting high-performance computing environments.

Infographic showing various Hpc Systems Engineer job openings in Michigan as of August 2026, with employment types broken down into 79% Full Time, 17% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

HPC AI Solution Architect (S2S)

Detroit, MI • On-site

Deloitte
Finance and Insurance • 10K+ employees

Full-time

Posted 7 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

48th of 154 rated financial services


Job description

Lead Cloud HPC- AI Infrastructure Architect(S2S)

As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team in Deloitte's AI & Engineering practice, you will design and drive deployment of fully integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure in close partnership with Deloitte AI specialists and our ecosystem partners. You will shape end-to-end solutions-from discovery and reference architecture mapping through sizing and implementation.  You will partner with Sales Executives, AI application specialists, delivery engineering, and managed services to help clients achieve measurable outcomes from private AI assets. You will lead technical solution strategy for pursuits and active opportunities and translate complex client needs into clear, complete solutions and delivery requirements.

Recruiting for this role ends on 10/3/2026.

Work you'll do
As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team, you will be responsible for:

  • Leading architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design
  • Creatively defining reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software and operations
  • Driving architecture trade-offs and decisions across performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk
  • Owning the technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach
  • Facilitating client workshops and technical reviews and translating engineering detail into executive-ready communications
  • Architecting complex, innovative technology solutions with a focus on business outcomes, cost of quality, and long-term scalability and sustainability.
  • Engaging with C-Suite client leadership during sales and delivery, including leading technical pre-sales discussions, shaping proposals, and supporting the closing of new business opportunities
  •  Supporting go-to-market strategies, including participation in industry events, conferences, and client briefings

The Team

The Silicon to Service team at Deloitte delivers end-to-end AI factories and advanced technology services that help organizations build, deploy, and operate large-scale, private AI and data platforms. We enable the next phase of enterprise AI adoption through private AI economics with cloud-like ese of use.  Join this unique opportunity to work on innovative AI platforms and emerging technologies in the rapidly evolving AI market while solving complex enterprise problems for some of the world's largest organizations.


Qualifications

Required:

  • 8+ years of experience in infrastructure architecture or engineering for large-scale platforms including design, implementation, operations, and optimization.
  • 4+ years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing
  • 3+ years Linux system administration in production environments
  • 3+ years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
  • 2+ years with high-performance networking or storage for AI/HPC
  • 2+ years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation
  • 2+ years automating infrastructure as code(IaC) with tools like Terraform and Ansible
  • At least 2 end-to-end deployments of reference architectures in the cloud or on-prem, including variants with security controls, network segmentation, operational runbooks, and validation testing
  • Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • 2+ years implementing AI/HPC cluster scheduling  (Slurm and Kubernetes), including multi-tenant queues, quotas, and GPU-aware policies
  • 2+ years supporting generative AI infrastructure patterns, including multi-node distributed training
  • Experience with AI agents and frameworks
  • Experience with high-throughput storage for AI/HPC
  • Experience executing NVIDIA co-sell motions with OEMS (Dell, HPC, Lenovo), CSPs ( AWS, Azure, Google Cloud), or independent software vendors ( Run:ai, OpenShift, Weights & Biases)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Lead Cloud HPC- AI Infrastructure Architect(S2S)

As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team in Deloitte's AI & Engineering practice, you will design and drive deployment of fully integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure in close partnership with Deloitte AI specialists and our ecosystem partners. You will shape end-to-end solutions-from discovery and reference architecture mapping through sizing and implementation.  You will partner with Sales Executives, AI application specialists, delivery engineering, and managed services to help clients achieve measurable outcomes from private AI assets. You will lead technical solution strategy for pursuits and active opportunities and translate complex client needs into clear, complete solutions and delivery requirements.

Recruiting for this role ends on 10/3/2026.

Work you'll do
As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team, you will be responsible for:

  • Leading architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design
  • Creatively defining reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software and operations
  • Driving architecture trade-offs and decisions across performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk
  • Owning the technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach
  • Facilitating client workshops and technical reviews and translating engineering detail into executive-ready communications
  • Architecting complex, innovative technology solutions with a focus on business outcomes, cost of quality, and long-term scalability and sustainability.
  • Engaging with C-Suite client leadership during sales and delivery, including leading technical pre-sales discussions, shaping proposals, and supporting the closing of new business opportunities
  •  Supporting go-to-market strategies, including participation in industry events, conferences, and client briefings

The Team

The Silicon to Service team at Deloitte delivers end-to-end AI factories and advanced technology services that help organizations build, deploy, and operate large-scale, private AI and data platforms. We enable the next phase of enterprise AI adoption through private AI economics with cloud-like ese of use.  Join this unique opportunity to work on innovative AI platforms and emerging technologies in the rapidly evolving AI market while solving complex enterprise problems for some of the world's largest organizations.


Qualifications

Required:

  • 8+ years of experience in infrastructure architecture or engineering for large-scale platforms including design, implementation, operations, and optimization.
  • 4+ years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing
  • 3+ years Linux system administration in production environments
  • 3+ years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
  • 2+ years with high-performance networking or storage for AI/HPC
  • 2+ years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation
  • 2+ years automating infrastructure as code(IaC) with tools like Terraform and Ansible
  • At least 2 end-to-end deployments of reference architectures in the cloud or on-prem, including variants with security controls, network segmentation, operational runbooks, and validation testing
  • Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • 2+ years implementing AI/HPC cluster scheduling  (Slurm and Kubernetes), including multi-tenant queues, quotas, and GPU-aware policies
  • 2+ years supporting generative AI infrastructure patterns, including multi-node distributed training
  • Experience with AI agents and frameworks
  • Experience with high-throughput storage for AI/HPC
  • Experience executing NVIDIA co-sell motions with OEMS (Dell, HPC, Lenovo), CSPs ( AWS, Azure, Google Cloud), or independent software vendors ( Run:ai, OpenShift, Weights & Biases)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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