LLM Infrastructure Engineer

Job not on LinkedIn

🔥 1 hour ago

🇦🇷 Argentina – Remote

💵 $2.5k - $4k / month

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hire Hangar Global

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Hire Hangar Global is a remote-first global recruitment and staffing marketplace that connects companies (from startups and tech firms to real estate and consulting agencies) with contract and full-time talent across marketing, sales, customer success, product, AI/data, and operational roles. The platform lists hundreds of remote positions across dozens of countries and supports hiring and scaling teams by offering sourcing, recruiting operations, and candidate placement services. Hire Hangar emphasizes flexible, contract-based engagements and positions itself as a hub for businesses looking to scale quickly and professionals seeking remote opportunities.

📋 Description

• Design, build, and maintain infrastructure for training, fine-tuning, and serving large language models • Deploy and scale LLM inference services for latency, throughput, and reliability • Manage GPU compute resources and optimize workload scheduling and utilization • Build and maintain data pipelines for model training and evaluation • Implement monitoring, logging, and alerting for model performance and system health • Optimize infrastructure costs while maintaining performance and availability • Automate deployment workflows using infrastructure-as-code and CI/CD practices • Collaborate with ML engineers and researchers to move models from experimentation into production • Identify bottlenecks, investigate root causes, and resolve infrastructure issues

🎯 Requirements

• Proven experience building large language model infrastructure (non-negotiable) • Hands-on experience deploying and serving machine learning models in production environments • Strong programming skills in Python, with experience in systems or backend development • Experience with Docker and Kubernetes • Solid understanding of distributed systems, GPU computing, and performance optimization • Strong written and spoken English with a clear, professional communication style • Prior remote work experience • Fluency with remote collaboration tools and platforms such as Slack, Zoom, Google Workspace, Asana, or similar • Ideally worked with US or UK-based companies • Strong AWS experience, including EC2, EKS, S3, and SageMaker • Prior experience at a large company or in enterprise-scale engineering environments • Familiarity with vLLM, TensorRT-LLM, or Triton Inference Server • Experience with Terraform or CloudFormation • Experience with PyTorch Distributed, DeepSpeed, or Ray

🏖️ Benefits

• Highly competitive, transparent compensation • Competitive, market-leading compensation • Long-term career opportunity • Growth opportunities