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Senior Infrastructure Engineer - AI/ML

U.S - Remote

Who We Are

We exist to unlock human potential.

Too often, AI drains it—drains budgets, drains energy resources, drains ownership of data. OpenTeams was founded to change that. We build AI that empowers. Our models are energy-efficient, cost-effective, and fully yours. 

Our ethos is open source. That means freedom, trust, and accountability are built into every line of code. We reinvest 3% of our profits back into the open-source community, because we believe tech is most powerful when it serves everyone.

At our core, we value freedom, teamwork, accountability, and uncompromising quality. If you want to fight Goliath, and shape tools that set people free, OpenTeams is the place to do it.

Job Title: Senior Infrastructure Engineer - AI/ML

Location: Remote (U.S. Preferred)

Work Authorization: Must be authorized to work in the United States

About the role

We are seeking a fully remote, experienced Senior Infrastructure Engineer to join our team at OpenTeams. At OpenTeams we prioritize cloud-native, reproducible, and observable infrastructure using tools like Terraform, Helm, ArgoCD, and Kubernetes operators. All of our infrastructure components are designed as reusable, composable building blocks that support AI/ML workflows including model training, inference serving, experiment tracking, and data processing pipelines using tools from the PyData ecosystem. These modular components can then be assembled into composable architectures that our clients maintain complete ownership and control over, creating truly sovereign AI infrastructure tailored to their specific requirements.

In this position, you'll get to:

  • Significantly contribute to the evolution of Nebari (https://nebari.dev) and design reusable, modular infrastructure components that can be composed into bespoke Kubernetes-based platforms for sovereign AI deployments
  • Develop composable MLOps components and infrastructure patterns supporting model training, serving, monitoring, and CI/CD pipelines that organizations can own and operate
  • Design and implement observability, monitoring, and cost optimization strategies for large-scale AI/ML workloads on client-owned Kubernetes infrastructure
  • Collaborate with ML engineers to optimize infrastructure for training ML models, quantizing and packaging open weight LLMs, computer vision workloads, and other AI applications in sovereign environments
  • Contribute to open-source MLOps tooling and Kubernetes ecosystem projects that enable data sovereignty
  • Work with clients to deploy, configure, and optimize their sovereign AI infrastructure
  • Collaborate with a fully remote distributed team using asynchronous communication methods

What We're Looking For

This is a senior role requiring significant experience in infrastructure engineering (or DevOps, SRE, Platform Engineering, or whatever we're calling it this week) and some level of technical leadership..

  • 4+ years of hands-on infrastructure/platform/DevOps experience with production systems
  • Strong understanding of infrastructure engineering principles: scalability, reliability, observability, and automation
  • Solid experience with Kubernetes in production environments, including troubleshooting and optimization
  • Proficiency with Infrastructure-as-Code tooling (Terraform, Helm, or similar) for managing complex deployments
  • Experience with at least one major cloud platform (AWS, Azure, GCP) including networking, security, and compute services
  • Strong programming skills, particularly in Python and/or Go, with ability to write maintainable infrastructure code
  • Experience contributing to technical initiatives or mentoring junior team members
  • Understanding of CI/CD practices, GitOps workflows, and infrastructure automation principles
  • Comfortable working independently and in distributed teams
  • Ability to provide and constructively receive feedback
  • Available for collaboration during overlap with US Central Time zone

Bonus points for experience with:

  • MLOps pipelines and ML infrastructure (model training, serving, monitoring)
  • Multiple cloud platforms and their AI/ML services
  • On-premises deployment and hybrid cloud environments
  • ML/AI ecosystem tools (PyTorch, TensorFlow, scikit-learn, etc.)
  • Monitoring and observability tools (Prometheus, Grafana, distributed tracing)
  • Data sovereignty, privacy, and security requirements for enterprise AI
  • GPU infrastructure and model serving frameworks (KServe, vLLM, LLM-D)
  • ML workflow orchestration tools (Kubeflow, MLflow, Airflow, Prefect)
  • Service mesh technologies (Istio, Linkerd) and advanced Kubernetes networking
  • Open-source contributions to Kubernetes, MLOps, or AI infrastructure projects
  • Cost optimization and resource management for ML workloads
  • Air-gapped or highly secure deployment environments

What matters most to us: We value diverse perspectives and recognize that expertise can be built through many different paths - whether through traditional tech roles, consulting, open source contributions, side projects, or cross-industry experience. If you have strong infrastructure engineering fundamentals and are passionate about sovereign AI infrastructure, we encourage you to apply even if your background doesn't look exactly like a traditional senior engineer path.

What We Offer

  • Medical, Dental & Vision – 100% paid for employees, 75% for dependents
  • 401(k) Match – Up to 5% with full vesting after 2 years
  • Unlimited PTO – With a required minimum of 15 days off annually
  • Fully Remote Setup – Includes up to $3,000 equipment reimbursement
  • Continuous Education –  Includes up to $500 reimbursement
  • Disability & Life Insurance – 100% employer-paid
  • HSA & FSA Options – With monthly HSA contributions from OpenTeams

Grow With Us

At OpenTeams, growth isn’t just about the company—it’s about you.

We believe the best careers are built at the edge of your potential. That is where new tools, ideas, and technologies change the world. Here, you’ll work alongside pioneers of AI, solving problems that matter: making AI more transparent, more ethical, and more empowering. 

Opportunities aren’t limited by geography. You’ll collaborate with global experts, contribute to open source projects that power the world’s technology, and stretch your skills daily.

We invest  in curiosity, creativity, and ownership. That means you’ll be trusted to take big swings, supported to learn fast, and celebrated for bold thinking.


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