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Vllm Jobs in Michigan (NOW HIRING)

Senior, ML Engineer - Auto Tagging

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference * Semantic Inference: Experience with semantic extraction and attribute mapping ...

Senior, ML Engineer - Auto Tagging

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference * Semantic Inference: Experience with semantic extraction and attribute mapping ...

Vllm information

What is a vLLM?

VLLM stands for 'Virtual Large Language Model.' In the context of AI development, VLLM professionals work with optimized inference engines for large language models, enabling faster and more efficient deployment of AI models in production environments. Their responsibilities often include integrating LLMs into applications, optimizing model performance, and ensuring scalability for real-time use cases. They may also collaborate with data scientists and engineers to manage resources and streamline AI workflows.

How does a vLLM engineer typically collaborate with data scientists and product teams during model deployment?

VLLM Engineers work closely with data scientists to understand the specific requirements and fine-tuning needs of large-scale language models. They are often responsible for integrating these models into production systems, ensuring scalability and efficiency. Collaboration with product teams is crucial to align model capabilities with user needs and to troubleshoot real-world application challenges. Frequent communication and agile workflows are common, as updates or optimizations may be needed rapidly based on feedback from both teams.

What are the key skills and qualifications needed to thrive as a machine learning engineer working with vLLM, and why are they important?

To thrive as a Machine Learning Engineer specializing in vLLM (a high-throughput LLM inference library), you need a strong understanding of machine learning principles, deep learning frameworks, and experience with Python programming. Familiarity with tools like PyTorch, CUDA, distributed computing, and cloud platforms, as well as relevant certifications in ML or data engineering, is highly valuable. Strong problem-solving, collaboration, and communication skills are essential for optimizing model performance and integrating with cross-functional teams. These capabilities ensure effective deployment and scaling of large language models, driving innovation and efficiency in AI applications.

What is the difference between Vllm vs Data Analyst?

AspectVllmData Analyst
Required CredentialsTypically requires knowledge of machine learning, AI, and programming languages like Python or RRequires skills in statistics, Excel, SQL, and data visualization tools
Work EnvironmentOften in tech companies, research labs, or AI-focused teamsCommonly in business, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and machine learning projectsEstablished role in data-driven decision making
Common Search/ComparisonVllm vs Data Analyst

The main difference between Vllm and Data Analyst lies in their focus and skill set. Vllm professionals specialize in AI and machine learning models, often working in tech environments, while Data Analysts focus on interpreting data to inform business decisions. Both roles require analytical skills, but Vllm roles demand programming and AI expertise, whereas Data Analysts emphasize statistical analysis and data visualization.

What job categories do people searching Vllm jobs in Michigan look for?

The top searched job categories for Vllm jobs in Michigan are:

What cities in Michigan are hiring for Vllm jobs?

Cities in Michigan with the most Vllm job openings:

Infographic showing various Vllm job openings in Michigan as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

AI Systems Engineer - AI Platforms - Manager

Southfield, MI • On-site

Other

Medical, Dental, Retirement, PTO

Posted yesterday

New


Job description

Location: Anywhere in Country

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

The opportunity

We are seeking AI Systems Engineers to build and operate the foundational substrate that powers EY’s AI-native platform. This role owns the infrastructure and cloud-native platform layers of the Hybrid AI Multi-Environment Runtime (HAI), from bare-metal and GPU infrastructure through Kubernetes, cluster fabric, and multi-tenant scaling. You will be responsible for building and managing EY Fabric environments across cloud, on-prem, edge, and air-gapped targets.

This is the substrate on which EY Agentic AI capabilities run. This role is ideal for a full-stack infrastructure leader who is equally comfortable with bare-metal and GPU systems and production Kubernetes at scale, who treats reliability and portability as non-negotiable in regulated client contexts, and who understands that the substrate is a product in its own right, measured by the velocity, safety, and portability it unlocks for every team building above it.

Your key responsibilities
  • Own the cluster & cloud-native platform: compute, Kubernetes and scheduling, cluster fabric/networking, multi-tenancy, and distributed compute, as the substrate for Agentic AI workflows and tooling.

  • Own the infrastructure foundation: Ubuntu/OS, BMC/bare-metal, DPU architecture, and NVAIE (GPU/Network/DCGM), ensuring the physical and virtual bedrock is provisioned, patched, and production-ready.

  • Stand up and manage EY Agentic AI environments across cloud (EKS/AKS/GKE), on-prem AI Factory (RKE2/NVAIE), edge (K3s), and air-gapped deployment modes, maintaining one consistent stack contract across all targets.
  • Deliver foundational platform capabilities such as Infrastructure Management, Kubernetes & Scheduling, and Cluster Fabric Management, so downstream runtime, data, and execution services can run safely and consistently.
  • Own cluster lifecycle, autoscaling, GPU pooling/virtualization, and multi-tenancy boundaries (vCluster/Crossplane/Karpenter), providing isolated, elastic capacity per tenant and engagement.
  • Own secure execution and inference: Ray Serve, vLLM/NIM/Triton, and NVIDIA Dynamo, with sandboxed execution (gVisor/Firecracker for hosted, NVIDIA OpenShell/vNode for on-prem) for isolated, safe model execution.
  • Own cognitive and routing: Envoy AI Gateway, semantic routing (vLLM-SR), model/prompt selection, and streaming response handling — directing each request to the right model under the right constraints.
  • Collaborate with DevOps Engineers on deployment and delivery of the platform itself: CI/CD/CV (ArgoCD), infrastructure‑as‑code / GitOps (Helm/OpenTofu), so environments are reproducible and drift‑free.
  • Own backup, disaster recovery, and cross‑environment replication for high availability (Velero, CloudNativePG, Cilium ClusterMesh), along with patching and platform supply‑chain hygiene.
  • Ensure the substrate is modular and swappable, so components can be replaced without rewriting consumers, minimizing vendor lock‑in while preserving the stack contract.
Skills and attributes for success
  • Deep expertise in cloud‑native platform engineering (Kubernetes, networking, multi‑tenancy at scale) and low‑level infrastructure and systems engineering (bare‑metal, GPU, DPU).
  • Advanced understanding of how compute, networking, storage, and scheduling interact to form a reliable, portable substrate.
  • Comfortable operating across cloud, on‑prem, edge, and air‑gapped environments simultaneously, with a portability‑first mindset.
  • Strong command of AI gateways, semantic routing, and model/prompt selection under latency and cost constraints.
  • A passion for ensuring reliability, repeatability, and reduction of operational toil through automation and infrastructure‑as‑code.
  • Ability to define and honor clean ownership boundaries with adjacent trust, data, and runtime teams.
  • Strong communicator able to explain infrastructure tradeoffs to engineers, architects, and leadership.
  • Natural product‑ownership orientation toward foundational platforms, measured by the downstream velocity and reliability they enable.
To qualify you must have
  • Bachelor’s or Master’s degree in Computer Science or related technical field.
  • 8+ years building or operating enterprise infrastructure, cloud platforms, or large‑scale Kubernetes environments, including hands‑on systems depth.
  • Hands‑on expertise with Kubernetes distributions (RKE2, EKS/AKS/GKE, K3s) and full cluster lifecycle management.
  • Deep experience with bare‑metal, cloud, hybrid, on‑prem, and ideally air‑gapped deployment models.
  • Strong grounding in cluster networking (Cilium/service mesh/CNI), storage, and multi‑tenancy isolation.
  • Experience with GPU infrastructure and scheduling (NVAIE/DCGM, GPU operators, virtualization/MIG).
  • Experience with infrastructure‑as‑code and GitOps tooling (Terraform/OpenTofu, Helm, ArgoCD, Crossplane).
  • Proven track record operating production infrastructure under compliance, security, or regulatory constraints.
  • Ability to work effectively with security, architecture, product, and delivery teams.
Ideally, you’ll also have
  • Experience supporting AI/ML and GPU‑intensive workloads (GPU virtualization, MIG, AI workload scheduling).
  • Experience with multi‑tenant platforms and tenancy isolation at scale (e.g., vCluster).
  • Experience with disaster recovery, backup, and cross‑environment replication tiered by RPO/RTO.
  • Familiarity with distributed compute and batch orchestration (Kueue, Slurm/Slinky, Ray, OpenMPI).
  • Background in platform or SRE roles where success is measured by downstream team velocity, reliability, and portability.
  • Exposure to regulated delivery environments (financial services, tax, healthcare, risk).
What we offer you

At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more .

  • We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $125,500 to $230,200. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $150,700 to $261,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
  • Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
  • Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being.

EY accepts applications for this position on an on‑going basis.

EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi‑disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at ssc.customersupport@ey.com .

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