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Vllm Jobs in Minnesota (NOW HIRING)

In Tandem

AI Engineer

Minneapolis, MN · On-site

$100K - $135K/yr

Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency. * Optimize aggressively: tensor ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One Holdings, LLC

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Sr. Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

System One

Data Scientist

Minneapolis, MN · On-site

Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. System One, and its ...

All JobsVllm JobsVllm Jobs in Minnesota

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 are popular job titles related to Vllm jobs in Minnesota?

For Vllm jobs in Minnesota, the most frequently searched job titles are:

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

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

What cities in Minnesota are hiring for Vllm jobs?

Cities in Minnesota with the most Vllm job openings:

Vllm jobs near you
Infographic showing various Vllm job openings in Minnesota as of August 2026, with employment types broken down into 94% Full Time, 1% Part Time, and 5% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

AI Engineer

In Tandem

Minneapolis, MN • On-site

$100K - $135K/yr

Full-time

Retirement, PTO

Re-posted 14 days ago

Job description

Description
At In Tandem, we build technology that helps families manage everyday routines and navigate life’s biggest transitions. Through our four brands—OurFamilyWizard, Cozi, FamilyWall, and Custody Navigator—we help families stay organized, communicate well, and foster healthy childhoods.  
We believe technology should strengthen relationships and make daily coordination less complicated. Everything we create is designed to lighten the mental load, reduce conflict, and support families through big and small moments.  
If you want your work to make a real difference in the daily lives of parents and kids, In Tandem is the place where your impact will truly matter.   
As our AI Engineer, you'll keep the AI infrastructure our products and teams run on fast, efficient, and reliable, and you'll build with it. You'll run and optimize our self-hosted inference stack on our own GPU hardware, build the internal platform our employees work through, and ship user-facing agents inside the apps. Your work spans OurFamilyWizard, Cozi, and FamilyWall, and the platforms that power how we build. 
This is a hands-on technical role at its core: you own the technical side of running our models on our own hardware. But it's not siloed, and we don't want it to be. We're looking for someone who also wants to pick up app-layer work and ship product-facing features, and does both well. 

What you will accomplish:
Run and optimize our self-hosted inference stack 
  • Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency. 
  • Optimize aggressively: tensor parallelism, quantization (FP8, AWQ, GPTQ), KV-cache and prefix caching, continuous batching, speculative decoding, concurrency tuning. 
  • Serve multiple models and features off shared hardware: multi-LoRA, routing, and request scheduling that balances internal workloads against latency-sensitive product traffic. 
Keep our AI fast, efficient, and observable 
  • Make our AI workloads efficient: improve latency, throughput, and GPU utilization so we get the most out of what we run. 
  • Build the visibility: instrument performance and usage across our AI surfaces so there's clear data on how everything is running. 
  • Surface the technical tradeoffs (performance, latency, efficiency) so the people making the calls have what they need to make them. 
Build AI features and proactive agents 
  • Ship the in-app agent layer that helps families coordinate: proactive nudges, smart suggestions, agents that summarize, draft, schedule, and act for busy parents. 
  • Build the substrate underneath: tools, memory, orchestration, guardrails, and evaluation harnesses, integrated cleanly with production APIs alongside our architecture team. 
  • Work in nimble pairs with feature owners, standing up whatever's needed to test an idea, including a vibe-coded UI when that's the fastest path to a real customer. Ship rough, learn fast, harden what works. 

Who you are:
  • Technical and hands-on with infrastructure: you like running real systems on real hardware and keeping them fast and reliable. 
  • A full-stack builder who wants the app layer too: you don't want to be boxed into infra. When a feature needs shipping, you want to pick it up and ship it, not just hand it off. 
  • Performance-minded: you treat latency, throughput, and efficiency as things to engineer deliberately. 
  • Rapid-prototyping and AI-first, with modern tooling (Claude Code, agent SDKs) part of your craft. 
  • Motivated by work that matters. Families rely on these products during real moments in their lives. 

What you bring:
  • 5+ years shipping production software, including meaningful applied AI or ML work. 
  • Demonstrated experience running and optimizing self-hosted LLMs on dedicated multi-GPU hardware: a serving stack (vLLM, SGLang, or TensorRT-LLM) and the optimization that comes with it (tensor parallelism, quantization, batching, KV cache). 
  • A track record of optimizing inference performance and efficiency (latency, throughput, GPU utilization). 
  • Strong Python and engineering fundamentals, with the full-stack range to stand up a quick UI, and the genuine desire to work app-layer features and not only infra. 
  • Hands-on with agent frameworks (Claude Agent SDK, LangGraph, or similar), LLM APIs, embeddings, and RAG. 
  • Comfortable with AWS and the devops this role owns: Docker, CI/CD, monitoring, and observability. 
  • Experience building internal tooling or platforms others depend on. Bonus for Slack apps, MCP, or agent orchestration at team scale. 
Why Join? 
We’re redefining family technology.  
In Tandem brings together a growing portfolio of trusted tools that support families, and the professionals who guide them, through the moments that matter most. We bring clarity to chaos and stability to daily family life, helping parents feel less stressed so kids can have healthier childhoods.  

Scale meets startup energy.  
With more than 20 years of impact and a strong market presence, we’re entering a bold new chapter of growth. We have the foundation, the momentum, and the ambition to go further: expanding our reach, deepening our impact, and elevating the tools families and professionals rely on every day.  
Purpose-driven. Performance-focused. People-first.  
Our culture is rooted in accountability, curiosity, and collaboration. We value diverse perspectives, thoughtful problem-solving, and teammates who care deeply about building something that matters. 
How we support you: 
  • Medical: In Tandem pays 100% of the premium for employees AND 99% for all additional family members 
  • 401k: Up to a 4% match with immediate vesting   
  • Paid leave for all new parents   
  • Learning & Development stipend for employees   
  • Paid Time Off: 11 Holidays + Winter Break (3 Days) + Volunteer Time Off (1 Day) + Floating Holiday (1 Day) 
  • Personal Time Off: 15 days for 0-1 years of employment, 20 days 1-3 years of employment
  • Supportive and flexible working environment – work from anywhere!   

Come As You Are! 
In Tandem provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.