This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Infrastructure Engineer - AI / ML in the United States .
This fully remote role offers the chance to design, implement, and optimize cutting-edge AI / ML infrastructure that empowers organizations to maintain full control over their data and compute resources. You will work on modular, cloud-native, and reusable infrastructure components supporting model training, inference serving, experiment tracking, and data pipelines. This high-impact position combines hands-on engineering with strategic influence, allowing you to shape scalable, secure, and observable systems while collaborating with a globally distributed team. The ideal candidate has strong experience in Kubernetes, cloud platforms, and Infrastructure-as-Code, and thrives in a culture that values autonomy, open source, and innovative thinking.
Accountabilities :
- Design, implement, and maintain modular, composable infrastructure components for AI / ML workflows including training, inference, and experiment tracking.
- Contribute to open-source MLOps tooling and Kubernetes ecosystem projects that enable data sovereignty and client-controlled AI platforms.
- Optimize large-scale AI / ML workloads for performance, cost efficiency, reliability, and observability on client-owned cloud and hybrid infrastructure.
- Collaborate with ML engineers, cross-functional teams, and clients to deploy, configure, and maintain sovereign AI infrastructure.
- Mentor junior engineers, contribute to technical initiatives, and provide feedback to uphold engineering excellence.
- Participate in designing CI / CD pipelines, GitOps workflows, and automation processes for scalable AI / ML systems.
Requirements
4+ years of hands-on infrastructure / platform / DevOps experience with production systems.Strong experience with Kubernetes, including troubleshooting, optimization, and production deployment.Proficiency with Infrastructure-as-Code tools such as Terraform, Helm, Pulumi, or Ansible.Experience with at least one major cloud platform (AWS, Azure, GCP), including networking, compute, and security.Strong programming skills in Python and / or Go for maintainable infrastructure code.Understanding of CI / CD practices, GitOps workflows, and automation principles.Ability to work independently in distributed teams and communicate effectively across time zones.Experience contributing to technical initiatives or mentoring junior engineers.Bonus experience : MLOps pipelines, model training and serving, monitoring tools (Prometheus, Grafana), GPU infrastructure, ML workflow orchestration (Kubeflow, MLflow, Airflow), service meshes, cost optimization, and secure deployment environments.Benefits
Fully remote U.S. work with up to $3,000 equipment reimbursement.Medical, dental, and vision insurance (100% employee coverage, 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.Disability and life insurance (100% employer-paid).HSA & FSA options with monthly HSA contributions.Continuous education reimbursement up to $500.Opportunity to work on open-source projects and cutting-edge sovereign AI infrastructure.Exposure to a global, distributed team fostering creativity, ownership, and innovation.Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score .
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
Our process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.
Thank you for your interest!
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